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Ser Nam Lim – Sernam Lim
Person information
- affiliation: Facebook AI, New York, NY, USA
- affiliation: Avitas Systems, GE Venture, Boston, MA, USA
- affiliation: GE Global Research, Niskayuna, NY, USA
- affiliation: Cognex Corp., Natick, MA, USA
- affiliation (PhD 2006): University of Maryland, College Park, MD, USA
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2020 – today
- 2024
[i101]Zhuoling Li, Xiaogang Xu, Ser-Nam Lim, Hengshuang Zhao:
UniMODE: Unified Monocular 3D Object Detection. CoRR abs/2402.18573 (2024)- [i100]Rukhshanda Hussain, Hui Xian Grace Lim, Borchun Chen, Mubarak Shah, Ser Nam Lim:
FSViewFusion: Few-Shots View Generation of Novel Objects. CoRR abs/2403.06394 (2024) - [i99]Lan Wang, Vishnu Boddeti, Sernam Lim:
Action Reimagined: Text-to-Pose Video Editing for Dynamic Human Actions. CoRR abs/2403.07198 (2024) - [i98]Dongmin Park, Zhaofang Qian, Guangxing Han, Ser-Nam Lim:
Mitigating Dialogue Hallucination for Large Multi-modal Models via Adversarial Instruction Tuning. CoRR abs/2403.10492 (2024) - [i97]Bo He, Hengduo Li, Young Kyun Jang, Menglin Jia, Xuefei Cao, Ashish Shah, Abhinav Shrivastava, Ser-Nam Lim:
MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding. CoRR abs/2404.05726 (2024) - [i96]Young Kyun Jang, Donghyun Kim, Zihang Meng, Dat Huynh, Ser-Nam Lim:
Visual Delta Generator with Large Multi-modal Models for Semi-supervised Composed Image Retrieval. CoRR abs/2404.15516 (2024) - [i95]Young Kyun Jang, Dat Huynh, Ashish Shah, Wen-Kai Chen, Ser-Nam Lim:
Spherical Linear Interpolation and Text-Anchoring for Zero-shot Composed Image Retrieval. CoRR abs/2405.00571 (2024) - [i94]Zhuoling Li, Xiaogang Xu, Zhenhua Xu, Ser-Nam Lim, Hengshuang Zhao:
LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence. CoRR abs/2405.17424 (2024) - 2023
- [c89]Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
Sample-Dependent Adaptive Temperature Scaling for Improved Calibration. AAAI 2023: 14919-14926 - [c88]Shishira R. Maiya, Max Ehrlich, Vatsal Agarwal, Ser-Nam Lim, Tom Goldstein, Abhinav Shrivastava:
Unifying the Harmonic Analysis of Adversarial Attacks and Robustness. BMVC 2023: 620-621 - [c87]Ameya Prabhu, Hasan Abed Al Kader Hammoud
, Puneet K. Dokania, Philip H. S. Torr, Ser-Nam Lim, Bernard Ghanem, Adel Bibi:
Computationally Budgeted Continual Learning: What Does Matter? CVPR 2023: 3698-3707 - [c86]Bo He, Xitong Yang, Hanyu Wang, Zuxuan Wu, Hao Chen, Shuaiyi Huang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava:
Towards Scalable Neural Representation for Diverse Videos. CVPR 2023: 6132-6142 - [c85]Hao Chen, Matthew Gwilliam, Ser-Nam Lim, Abhinav Shrivastava:
HNeRV: A Hybrid Neural Representation for Videos. CVPR 2023: 10270-10279 - [c84]Zhenyu Wang, Yali Li, Xi Chen, Ser-Nam Lim, Antonio Torralba, Hengshuang Zhao, Shengjin Wang:
Detecting Everything in the Open World: Towards Universal Object Detection. CVPR 2023: 11433-11443 - [c83]Jishnu Mukhoti, Tsung-Yu Lin, Omid Poursaeed, Rui Wang, Ashish Shah, Philip H. S. Torr, Ser-Nam Lim:
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning. CVPR 2023: 19413-19423 - [c82]A. Tuan Nguyen, Thanh Nguyen-Tang, Ser-Nam Lim, Philip H. S. Torr:
TIPI: Test Time Adaptation with Transformation Invariance. CVPR 2023: 24162-24171 - [c81]Xi Chen, Shuang Li, Ser-Nam Lim, Antonio Torralba, Hengshuang Zhao:
Open-vocabulary Panoptic Segmentation with Embedding Modulation. ICCV 2023: 1141-1150 - [c80]Yifei Zhou, Zilu Li, Abhinav Shrivastava, Hengshuang Zhao, Antonio Torralba, Tai-Peng Tian, Ser-Nam Lim:
BT2: Backward-compatible Training with Basis Transformation. ICCV 2023: 11195-11204 - [c79]Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim, Philip H. S. Torr, Adel Bibi, Bernard Ghanem:
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? ICCV 2023: 18806-18815 - [c78]Mohamed Afham, Satya Narayan Shukla, Omid Poursaeed, Pengchuan Zhang, Ashish Shah, Sernam Lim:
Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding. ICCV (Workshops) 2023: 1181-1186 - [c77]Jishnu Mukhoti, Tsung-Yu Lin, Bor-Chun Chen, Ashish Shah, Philip H. S. Torr, Puneet K. Dokania, Ser-Nam Lim:
Raising the Bar on the Evaluation of Out-of-Distribution Detection. ICCV (Workshops) 2023: 4367-4377 - [c76]Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim:
Graph Inductive Biases in Transformers without Message Passing. ICML 2023: 23321-23337 - [c75]Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher De Sa:
Riemannian Residual Neural Networks. NeurIPS 2023 - [c74]Gaurav Shrivastava, Ser Nam Lim, Abhinav Shrivastava:
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements. NeurIPS 2023 - [c73]Yifei Zhou, Juntao Ren, Fengyu Li, Ramin Zabih, Ser Nam Lim:
Test-Time Distribution Normalization for Contrastively Learned Visual-language Models. NeurIPS 2023 - [i93]Seonguk Seo, Mustafa Gökhan Uzunbas, Bohyung Han, Sara Cao, Joena Zhang, Tai-Peng Tian, Ser-Nam Lim:
Online Backfilling with No Regret for Large-Scale Image Retrieval. CoRR abs/2301.03767 (2023) - [i92]Yifei Zhou, Juntao Ren, Fengyu Li, Ramin Zabih, Ser-Nam Lim:
Distribution Normalization: An "Effortless" Test-Time Augmentation for Contrastively Learned Visual-language Models. CoRR abs/2302.11084 (2023) - [i91]Ameya Prabhu, Hasan Abed Al Kader Hammoud, Puneet K. Dokania, Philip H. S. Torr, Ser-Nam Lim, Bernard Ghanem, Adel Bibi:
Computationally Budgeted Continual Learning: What Does Matter? CoRR abs/2303.11165 (2023) - [i90]Xi Chen, Yau Shing Jonathan Cheung, Ser-Nam Lim, Hengshuang Zhao:
ScribbleSeg: Scribble-based Interactive Image Segmentation. CoRR abs/2303.11320 (2023) - [i89]Xi Chen, Shuang Li, Ser-Nam Lim, Antonio Torralba, Hengshuang Zhao:
Open-vocabulary Panoptic Segmentation with Embedding Modulation. CoRR abs/2303.11324 (2023) - [i88]Zhenyu Wang, Yali Li, Xi Chen, Ser-Nam Lim, Antonio Torralba, Hengshuang Zhao, Shengjin Wang:
Detecting Everything in the Open World: Towards Universal Object Detection. CoRR abs/2303.11749 (2023) - [i87]Bo He, Xitong Yang, Hanyu Wang, Zuxuan Wu, Hao Chen, Shuaiyi Huang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava:
Towards Scalable Neural Representation for Diverse Videos. CoRR abs/2303.14124 (2023) - [i86]Zhuoling Li, Chuanrui Zhang, Wei-Chiu Ma, Yipin Zhou, Linyan Huang, Haoqian Wang, Ser-Nam Lim, Hengshuang Zhao:
VoxelFormer: Bird's-Eye-View Feature Generation based on Dual-view Attention for Multi-view 3D Object Detection. CoRR abs/2304.01054 (2023) - [i85]Hao Chen, Matthew Gwilliam, Ser-Nam Lim, Abhinav Shrivastava:
HNeRV: A Hybrid Neural Representation for Videos. CoRR abs/2304.02633 (2023) - [i84]Jiani Huang, Ziyang Li, David Jacobs, Mayur Naik, Ser-Nam Lim:
LASER: Neuro-Symbolic Learning of Semantic Video Representations. CoRR abs/2304.07647 (2023) - [i83]Hasan Abed Al Kader Hammoud, Ameya Prabhu, Ser-Nam Lim, Philip H. S. Torr, Adel Bibi, Bernard Ghanem:
Rapid Adaptation in Online Continual Learning: Are We Evaluating It Right? CoRR abs/2305.09275 (2023) - [i82]Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim:
Graph Inductive Biases in Transformers without Message Passing. CoRR abs/2305.17589 (2023) - [i81]Xiao Liu, Guangyi Chen, Yansong Tang, Guangrun Wang, Ser-Nam Lim:
Language-free Compositional Action Generation via Decoupling Refinement. CoRR abs/2307.03538 (2023) - [i80]Mohamed Afham, Satya Narayan Shukla, Omid Poursaeed, Pengchuan Zhang, Ashish Shah, Sernam Lim:
Revisiting Kernel Temporal Segmentation as an Adaptive Tokenizer for Long-form Video Understanding. CoRR abs/2309.11569 (2023) - [i79]Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser-Nam Lim, Christopher De Sa:
Riemannian Residual Neural Networks. CoRR abs/2310.10013 (2023) - [i78]Ameya Prabhu, Hasan Abed Al Kader Hammoud, Ser-Nam Lim, Bernard Ghanem, Philip H. S. Torr, Adel Bibi:
From Categories to Classifier: Name-Only Continual Learning by Exploring the Web. CoRR abs/2311.11293 (2023) - [i77]Botos Csaba, Wenxuan Zhang, Matthias Müller, Ser-Nam Lim, Mohamed Elhoseiny, Philip H. S. Torr, Adel Bibi:
Label Delay in Continual Learning. CoRR abs/2312.00923 (2023) - [i76]Piotr Teterwak, Ximeng Sun, Bryan A. Plummer, Kate Saenko, Ser-Nam Lim:
CLAMP: Contrastive LAnguage Model Prompt-tuning. CoRR abs/2312.01629 (2023) - [i75]Kaiyu Yue, Bor-Chun Chen, Jonas Geiping, Hengduo Li, Tom Goldstein, Ser-Nam Lim:
Object Recognition as Next Token Prediction. CoRR abs/2312.02142 (2023) - [i74]Xuanming Cui, Alejandro Aparcedo, Young Kyun Jang, Ser-Nam Lim:
On the Robustness of Large Multimodal Models Against Image Adversarial Attacks. CoRR abs/2312.03777 (2023) - [i73]Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava:
Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements. CoRR abs/2312.07835 (2023) - [i72]Shraman Pramanick, Guangxing Han, Rui Hou, Sayan Nag, Ser-Nam Lim, Nicolas Ballas, Qifan Wang, Rama Chellappa, Amjad Almahairi:
Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine Vision-Language Model. CoRR abs/2312.12423 (2023) - [i71]Ping-yeh Chiang, Yipin Zhou, Omid Poursaeed, Satya Narayan Shukla, Ashish Shah, Tom Goldstein, Ser-Nam Lim:
Universal Pyramid Adversarial Training for Improved ViT Performance. CoRR abs/2312.16339 (2023) - 2022
- [c72]Hao Chen, Matthew Gwilliam, Bo He, Ser-Nam Lim, Abhinav Shrivastava:
CNeRV: Content-adaptive Neural Representation for Visual Data. BMVC 2022: 510 - [c71]Boyi Li, Serge J. Belongie, Ser-Nam Lim, Abe Davis:
Neural Image Recolorization for Creative Domains. CVPR Workshops 2022: 2225-2229 - [c70]Junke Wang, Zuxuan Wu, Jingjing Chen, Xintong Han, Abhinav Shrivastava, Ser-Nam Lim, Yu-Gang Jiang:
ObjectFormer for Image Manipulation Detection and Localization. CVPR 2022: 2354-2363 - [c69]Lingchen Meng, Hengduo Li, Bor-Chun Chen, Shiyi Lan, Zuxuan Wu, Yu-Gang Jiang, Ser-Nam Lim:
AdaViT: Adaptive Vision Transformers for Efficient Image Recognition. CVPR 2022: 12299-12308 - [c68]Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba:
Totems: Physical Objects for Verifying Visual Integrity. ECCV (14) 2022: 164-180 - [c67]Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim:
Object-Centric Unsupervised Image Captioning. ECCV (36) 2022: 219-235 - [c66]Xiaogang Xu, Hengshuang Zhao, Vibhav Vineet, Ser-Nam Lim, Antonio Torralba:
MTFormer: Multi-task Learning via Transformer and Cross-Task Reasoning. ECCV (27) 2022: 304-321 - [c65]Tohar Lukov, Na Zhao, Gim Hee Lee, Ser-Nam Lim:
Teaching with Soft Label Smoothing for Mitigating Noisy Labels in Facial Expressions. ECCV (12) 2022: 648-665 - [c64]Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge J. Belongie, Bharath Hariharan, Ser-Nam Lim:
Visual Prompt Tuning. ECCV (33) 2022: 709-727 - [c63]Botos Csaba, Adel Bibi, Yanwei Li, Philip H. S. Torr, Ser-Nam Lim:
Diversified Dynamic Routing for Vision Tasks. ECCV Workshops (4) 2022: 756-772 - [c62]Junke Wang, Zuxuan Wu, Wenhao Ouyang, Xintong Han, Jingjing Chen, Yu-Gang Jiang, Ser-Nam Lim:
M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection. ICMR 2022: 615-623 - [c61]A. Tuan Nguyen, Philip H. S. Torr, Ser Nam Lim:
FedSR: A Simple and Effective Domain Generalization Method for Federated Learning. NeurIPS 2022 - [c60]Francesco Pinto, Harry Yang, Ser Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness. NeurIPS 2022 - [c59]Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou, Ser-Nam Lim, Jiwen Lu:
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions. NeurIPS 2022 - [c58]Kai Sheng Tai, Tai-Peng Tian, Ser Nam Lim:
Spartan: Differentiable Sparsity via Regularized Transportation. NeurIPS 2022 - [c57]Ze Wang, Yipin Zhou, Rui Wang, Tsung-Yu Lin, Ashish Shah, Ser Nam Lim:
Few-Shot Fast-Adaptive Anomaly Detection. NeurIPS 2022 - [c56]Yifei Zhou, Renyu Li, Hayden Housen, Ser Nam Lim:
GAPX: Generalized Autoregressive Paraphrase-Identification X. NeurIPS 2022 - [i70]A. Tuan Nguyen, Ser Nam Lim, Philip H. S. Torr:
Task-Agnostic Robust Representation Learning. CoRR abs/2203.07596 (2022) - [i69]Menglin Jia, Luming Tang, Bor-Chun Chen, Claire Cardie, Serge J. Belongie, Bharath Hariharan, Ser-Nam Lim:
Visual Prompt Tuning. CoRR abs/2203.12119 (2022) - [i68]Junke Wang, Zuxuan Wu, Jingjing Chen, Xintong Han, Abhinav Shrivastava, Ser-Nam Lim, Yu-Gang Jiang:
ObjectFormer for Image Manipulation Detection and Localization. CoRR abs/2203.14681 (2022) - [i67]Kennard Ng, Ser-Nam Lim, Gim Hee Lee:
VRAG: Region Attention Graphs for Content-Based Video Retrieval. CoRR abs/2205.09068 (2022) - [i66]Kai Sheng Tai, Tai-Peng Tian, Ser-Nam Lim:
Spartan: Differentiable Sparsity via Regularized Transportation. CoRR abs/2205.14107 (2022) - [i65]Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness. CoRR abs/2206.14502 (2022) - [i64]Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania:
Sample-dependent Adaptive Temperature Scaling for Improved Calibration. CoRR abs/2207.06211 (2022) - [i63]Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou, Ser-Nam Lim, Jiwen Lu:
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions. CoRR abs/2207.14284 (2022) - [i62]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
Benchmarking Validation Methods for Unsupervised Domain Adaptation. CoRR abs/2208.07360 (2022) - [i61]Jishnu Mukhoti, Tsung-Yu Lin, Bor-Chun Chen, Ashish Shah, Philip H. S. Torr, Puneet K. Dokania, Ser-Nam Lim:
Raising the Bar on the Evaluation of Out-of-Distribution Detection. CoRR abs/2209.11960 (2022) - [i60]Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba:
Totems: Physical Objects for Verifying Visual Integrity. CoRR abs/2209.13032 (2022) - [i59]Botos Csaba, Adel Bibi, Yanwei Li, Philip H. S. Torr, Ser-Nam Lim:
Diversified Dynamic Routing for Vision Tasks. CoRR abs/2209.13071 (2022) - [i58]Yifei Zhou, Renyu Li, Hayden Housen, Ser-Nam Lim:
GAPX: Generalized Autoregressive Paraphrase-Identification X. CoRR abs/2210.01979 (2022) - [i57]Yifei Zhou, Zilu Li, Abhinav Shrivastava, Hengshuang Zhao, Antonio Torralba, Tai-Peng Tian, Ser-Nam Lim:
BT2: Backward-compatible Training with Basis Transformation. CoRR abs/2211.03989 (2022) - [i56]Hao Chen, Matthew Gwilliam, Bo He, Ser-Nam Lim, Abhinav Shrivastava:
CNeRV: Content-adaptive Neural Representation for Visual Data. CoRR abs/2211.10421 (2022) - [i55]Peirong Liu, Rui Wang, Pengchuan Zhang, Omid Poursaeed, Yipin Zhou, Xuefei Cao, Sreya Dutta Roy, Ashish Shah, Ser-Nam Lim:
A Unified Model for Tracking and Image-Video Detection Has More Power. CoRR abs/2211.11077 (2022) - [i54]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
PyTorch Adapt. CoRR abs/2211.15673 (2022) - [i53]Jishnu Mukhoti, Tsung-Yu Lin, Omid Poursaeed, Rui Wang, Ashish Shah, Philip H. S. Torr, Ser-Nam Lim:
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning. CoRR abs/2212.04994 (2022) - 2021
- [c55]Peng Zhou, Ning Yu, Zuxuan Wu, Larry Davis, Abhinav Shrivastava, Ser-Nam Lim:
Deep Video Inpainting Detection. BMVC 2021: 35 - [c54]Bo He, Xitong Yang, Zuxuan Wu, Hao Chen, Ser-Nam Lim, Abhinav Shrivastava:
GTA: Global Temporal Attention for Video Action Understanding. BMVC 2021: 292 - [c53]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CVPR 2021: 12383-12392 - [c52]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Intentonomy: A Dataset and Study Towards Human Intent Understanding. CVPR 2021: 12986-12996 - [c51]Bor-Chun Chen, Zuxuan Wu, Larry S. Davis, Ser-Nam Lim:
Efficient Object Embedding for Spliced Image Retrieval. CVPR 2021: 14965-14975 - [c50]Shir Gur, Natalia Neverova, Christopher Stauffer, Ser-Nam Lim, Douwe Kiela, Austin Reiter:
Cross-Modal Retrieval Augmentation for Multi-Modal Classification. EMNLP (Findings) 2021: 111-123 - [c49]Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoav Artzi, Claire Cardie:
When in Doubt: Improving Classification Performance with Alternating Normalization. EMNLP (Findings) 2021: 1716-1723 - [c48]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Exploring Visual Engagement Signals for Representation Learning. ICCV 2021: 4186-4197 - [c47]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation. ICCV 2021: 8886-8896 - [c46]Yipin Zhou, Ser-Nam Lim:
Joint Audio-Visual Deepfake Detection. ICCV 2021: 14780-14789 - [c45]Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge J. Belongie, Ser-Nam Lim:
Robustness and Generalization via Generative Adversarial Training. ICCV 2021: 15691-15700 - [c44]Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava:
Analyzing and Mitigating JPEG Compression Defects in Deep Learning. ICCVW 2021: 2357-2367 - [c43]Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin R. Benson:
Combining Label Propagation and Simple Models out-performs Graph Neural Networks. ICLR 2021 - [c42]Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Equivariant Manifold Flows. NeurIPS 2021: 10600-10612 - [c41]Keyu Tian, Chen Lin, Ser-Nam Lim, Wanli Ouyang, Puneet K. Dokania, Philip H. S. Torr:
A Continuous Mapping For Augmentation Design. NeurIPS 2021: 13732-13743 - [c40]Toru Lin, Jacob Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola:
Learning to Ground Multi-Agent Communication with Autoencoders. NeurIPS 2021: 15230-15242 - [c39]Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim:
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. NeurIPS 2021: 20887-20902 - [c38]Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava:
NeRV: Neural Representations for Videos. NeurIPS 2021: 21557-21568 - [i52]Peng Zhou, Ning Yu, Zuxuan Wu, Larry S. Davis, Abhinav Shrivastava, Ser-Nam Lim:
Deep Video Inpainting Detection. CoRR abs/2101.11080 (2021) - [i51]Zuxuan Wu, Tom Goldstein, Larry S. Davis, Ser-Nam Lim:
THAT: Two Head Adversarial Training for Improving Robustness at Scale. CoRR abs/2103.13612 (2021) - [i50]Derek Lim, Xiuyu Li, Felix Hohne, Ser-Nam Lim:
New Benchmarks for Learning on Non-Homophilous Graphs. CoRR abs/2104.01404 (2021) - [i49]Sethuraman Sankaran, David Yang, Ser-Nam Lim:
Multimodal Fusion Refiner Networks. CoRR abs/2104.03435 (2021) - [i48]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Exploring Visual Engagement Signals for Representation Learning. CoRR abs/2104.07767 (2021) - [i47]Shir Gur, Natalia Neverova, Christopher Stauffer, Ser-Nam Lim, Douwe Kiela, Austin Reiter:
Cross-Modal Retrieval Augmentation for Multi-Modal Classification. CoRR abs/2104.08108 (2021) - [i46]Abhay Singh, Qian Huang, Sijia Linda Huang, Omkar Bhalerao, Horace He, Ser-Nam Lim, Austin R. Benson:
Edge Proposal Sets for Link Prediction. CoRR abs/2106.15810 (2021) - [i45]Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Equivariant Manifold Flows. CoRR abs/2107.08596 (2021) - [i44]Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge J. Belongie, Ser-Nam Lim:
Robustness and Generalization via Generative Adversarial Training. CoRR abs/2109.02765 (2021) - [i43]Menglin Jia, Austin Reiter, Ser-Nam Lim, Yoav Artzi, Claire Cardie:
When in Doubt: Improving Classification Performance with Alternating Normalization. CoRR abs/2109.13449 (2021) - [i42]Peirong Liu, Rui Wang, Xuefei Cao, Yipin Zhou, Ashish Shah, Maxime Oquab, Camille Couprie, Ser-Nam Lim:
Self-appearance-aided Differential Evolution for Motion Transfer. CoRR abs/2110.04658 (2021) - [i41]Xuefeng Hu, M. Gökhan Uzunbas, Sirius Chen, Rui Wang, Ashish Shah, Ram Nevatia, Ser-Nam Lim:
MixNorm: Test-Time Adaptation Through Online Normalization Estimation. CoRR abs/2110.11478 (2021) - [i40]Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava:
NeRV: Neural Representations for Videos. CoRR abs/2110.13903 (2021) - [i39]Derek Lim, Felix Hohne, Xiuyu Li, Sijia Linda Huang, Vaishnavi Gupta, Omkar Bhalerao, Ser-Nam Lim:
Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. CoRR abs/2110.14446 (2021) - [i38]Toru Lin, Minyoung Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola:
Learning to Ground Multi-Agent Communication with Autoencoders. CoRR abs/2110.15349 (2021) - [i37]Shishira R. Maiya, Max Ehrlich, Vatsal Agarwal, Ser-Nam Lim, Tom Goldstein, Abhinav Shrivastava:
A Frequency Perspective of Adversarial Robustness. CoRR abs/2111.00861 (2021) - [i36]Lingchen Meng, Hengduo Li, Bor-Chun Chen, Shiyi Lan, Zuxuan Wu, Yu-Gang Jiang, Ser-Nam Lim:
AdaViT: Adaptive Vision Transformers for Efficient Image Recognition. CoRR abs/2111.15668 (2021) - [i35]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
Unsupervised Domain Adaptation: A Reality Check. CoRR abs/2111.15672 (2021) - [i34]Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim:
Object-Centric Unsupervised Image Captioning. CoRR abs/2112.00969 (2021) - [i33]Menglin Jia, Bor-Chun Chen, Zuxuan Wu, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Rethinking Nearest Neighbors for Visual Classification. CoRR abs/2112.08459 (2021) - 2020
- [c37]Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser-Nam Lim, Larry Davis:
Generate, Segment, and Refine: Towards Generic Manipulation Segmentation. AAAI 2020: 13058-13065 - [c36]Chao Yang, Ser-Nam Lim:
One-Shot Domain Adaptation for Face Generation. CVPR 2020: 5920-5929 - [c35]Zuxuan Wu, Ser-Nam Lim, Larry S. Davis, Tom Goldstein:
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors. ECCV (4) 2020: 1-17 - [c34]Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What Makes Fake Images Detectable? Understanding Properties that Generalize. ECCV (26) 2020: 103-120 - [c33]Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava:
Quantization Guided JPEG Artifact Correction. ECCV (8) 2020: 293-309 - [c32]Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava:
Curriculum Manager for Source Selection in Multi-source Domain Adaptation. ECCV (14) 2020: 608-624 - [c31]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
A Metric Learning Reality Check. ECCV (25) 2020: 681-699 - [c30]Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa:
Differentiating through the Fréchet Mean. ICML 2020: 6393-6403 - [c29]Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin R. Benson:
Better Set Representations For Relational Reasoning. NeurIPS 2020 - [c28]Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Neural Manifold Ordinary Differential Equations. NeurIPS 2020 - [c27]Shruti Agarwal, Hany Farid, Tarek El-Gaaly, Ser-Nam Lim:
Detecting Deep-Fake Videos from Appearance and Behavior. WIFS 2020: 1-6 - [i32]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CoRR abs/2002.11102 (2020) - [i31]Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa:
Differentiating through the Fréchet Mean. CoRR abs/2003.00335 (2020) - [i30]Austin Reiter, Menglin Jia, Pu Yang, Ser-Nam Lim:
Deep Multi-Modal Sets. CoRR abs/2003.01607 (2020) - [i29]Qian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin R. Benson:
Set-Structured Latent Representations. CoRR abs/2003.04448 (2020) - [i28]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
A Metric Learning Reality Check. CoRR abs/2003.08505 (2020) - [i27]Chao Yang, Ser-Nam Lim:
One-Shot Domain Adaptation For Face Generation. CoRR abs/2003.12869 (2020) - [i26]Max Ehrlich, Ser-Nam Lim, Larry Davis, Abhinav Shrivastava:
Quantization Guided JPEG Artifact Correction. CoRR abs/2004.09320 (2020) - [i25]Shruti Agarwal, Tarek El-Gaaly, Hany Farid, Ser-Nam Lim:
Detecting Deep-Fake Videos from Appearance and Behavior. CoRR abs/2004.14491 (2020) - [i24]Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa:
Neural Manifold Ordinary Differential Equations. CoRR abs/2006.10254 (2020) - [i23]Luyu Yang, Yogesh Balaji, Ser-Nam Lim, Abhinav Shrivastava:
Curriculum Manager for Source Selection in Multi-Source Domain Adaptation. CoRR abs/2007.01261 (2020) - [i22]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation. CoRR abs/2007.12684 (2020) - [i21]Kevin Musgrave, Serge J. Belongie, Ser-Nam Lim:
PyTorch Metric Learning. CoRR abs/2008.09164 (2020) - [i20]Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What makes fake images detectable? Understanding properties that generalize. CoRR abs/2008.10588 (2020) - [i19]Qian Huang, Horace He, Abhay Singh, Ser-Nam Lim, Austin R. Benson:
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks. CoRR abs/2010.13993 (2020) - [i18]Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge J. Belongie, Ser-Nam Lim:
Intentonomy: a Dataset and Study towards Human Intent Understanding. CoRR abs/2011.05558 (2020) - [i17]Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava:
Analyzing and Mitigating Compression Defects in Deep Learning. CoRR abs/2011.08932 (2020) - [i16]Bo He, Xitong Yang, Zuxuan Wu, Hao Chen, Ser-Nam Lim, Abhinav Shrivastava:
GTA: Global Temporal Attention for Video Action Understanding. CoRR abs/2012.08510 (2020)
2010 – 2019
- 2019
- [c26]Qian Huang, Isay Katsman, Zeqi Gu, Horace He, Serge J. Belongie, Ser-Nam Lim:
Enhancing Adversarial Example Transferability With an Intermediate Level Attack. ICCV 2019: 4732-4741 - [c25]Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry Davis, Jun Li, Jian Yang, Ser-Nam Lim:
Cross-X Learning for Fine-Grained Visual Categorization. ICCV 2019: 8241-8250 - [i15]Bor-Chun Chen, Larry S. Davis, Ser-Nam Lim:
An Analysis of Object Embeddings for Image Retrieval. CoRR abs/1905.11903 (2019) - [i14]Qian Huang, Isay Katsman, Horace He, Zeqi Gu, Serge J. Belongie, Ser-Nam Lim:
Enhancing Adversarial Example Transferability with an Intermediate Level Attack. CoRR abs/1907.10823 (2019) - [i13]Wei Luo, Xitong Yang, Xianjie Mo, Yuheng Lu, Larry S. Davis, Jun Li, Jian Yang, Ser-Nam Lim:
Cross-X Learning for Fine-Grained Visual Categorization. CoRR abs/1909.04412 (2019) - [i12]Zuxuan Wu, Ser-Nam Lim, Larry Davis, Tom Goldstein:
Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors. CoRR abs/1910.14667 (2019) - [i11]Xuefei Cao, Bor-Chun Chen, Ser-Nam Lim:
Unsupervised Deep Metric Learning via Auxiliary Rotation Loss. CoRR abs/1911.07072 (2019) - [i10]Omid Poursaeed, Tianxing Jiang, Harry Yang, Serge J. Belongie, Ser-Nam Lim:
Fine-grained Synthesis of Unrestricted Adversarial Examples. CoRR abs/1911.09058 (2019) - [i9]Chao Yang, Ser-Nam Lim:
Unconstrained Facial Expression Transfer using Style-based Generator. CoRR abs/1912.06253 (2019) - [i8]Yin Cui, Zeqi Gu, Dhruv Mahajan, Laurens van der Maaten, Serge J. Belongie, Ser-Nam Lim:
Measuring Dataset Granularity. CoRR abs/1912.10154 (2019) - 2018
- [c24]Swami Sankaranarayanan, Arpit Jain, Rama Chellappa, Ser-Nam Lim:
Regularizing Deep Networks Using Efficient Layerwise Adversarial Training. AAAI 2018: 4008-4015 - [c23]Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, Rama Chellappa:
Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation. CVPR 2018: 3752-3761 - [c22]Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gökhan Uzunbas, Tom Goldstein, Ser-Nam Lim, Larry S. Davis:
DCAN: Dual Channel-Wise Alignment Networks for Unsupervised Scene Adaptation. ECCV (5) 2018: 535-552 - [c21]Yi Wei, Ming-Ching Chang, Yiming Ying, Ser Nam Lim, Siwei Lyu:
Explain Black-box Image Classifications Using Superpixel-based Interpretation. ICPR 2018: 1640-1645 - [i7]Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gökhan Uzunbas, Tom Goldstein, Ser-Nam Lim, Larry S. Davis:
DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation. CoRR abs/1804.05827 (2018) - [i6]Qian Huang, Zeqi Gu, Isay Katsman, Horace He, Pian Pawakapan, Zhiqiu Lin, Serge J. Belongie, Ser-Nam Lim:
Intermediate Level Adversarial Attack for Enhanced Transferability. CoRR abs/1811.08458 (2018) - [i5]Horace He, Aaron Lou, Qingxuan Jiang, Isay Katsman, Pian Pawakapan, Serge J. Belongie, Ser-Nam Lim:
Adversarial Example Decomposition. CoRR abs/1812.01198 (2018) - 2017
- [c20]Mustafa Devrim Kaba, Mustafa Gökhan Uzunbas, Ser-Nam Lim:
A Reinforcement Learning Approach to the View Planning Problem. CVPR 2017: 5094-5102 - [c19]Wenbo Li, Longyin Wen, Ming-Ching Chang, Ser Nam Lim, Siwei Lyu:
Adaptive RNN Tree for Large-Scale Human Action Recognition. ICCV 2017: 1453-1461 - [c18]Swami Sankaranarayanan, Arpit Jain, Ser Nam Lim:
Guided Perturbations: Self-Corrective Behavior in Convolutional Neural Networks. ICCV 2017: 3582-3590 - [i4]Swami Sankaranarayanan, Arpit Jain, Ser Nam Lim:
Guided Perturbations: Self Corrective Behavior in Convolutional Neural Networks. CoRR abs/1703.07928 (2017) - [i3]Swami Sankaranarayanan, Arpit Jain, Rama Chellappa, Ser-Nam Lim:
Regularizing deep networks using efficient layerwise adversarial training. CoRR abs/1705.07819 (2017) - [i2]Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser-Nam Lim, Rama Chellappa:
Unsupervised Domain Adaptation for Semantic Segmentation with GANs. CoRR abs/1711.06969 (2017) - 2016
- [c17]Wei Wang, Kun Duan, Tai-Peng Tian, Ting Yu, Ser Nam Lim, Hairong Qi:
Visual tracking based on object appearance and structure preserved local patches matching. AVSS 2016: 145-151 - [c16]Xiao Bian, Ser-Nam Lim, Ning Zhou:
Multiscale fully convolutional network with application to industrial inspection. WACV 2016: 1-8 - [c15]Ser-Nam Lim, Joao Soares, Ning Zhou:
Tooth guard: A vision system for detecting missing tooth in rope mine shovel. WACV 2016: 1-7 - [i1]Mustafa Devrim Kaba, Mustafa Gökhan Uzunbas, Ser-Nam Lim:
A Reinforcement Learning Approach to Sensor Planning for 3D Models. CoRR abs/1610.06204 (2016) - 2013
- [c14]Ser-Nam Lim, Li Guan, Shubao Liu, Xingwei Yang:
Automatic Registration of Smooth Object Image to 3D CAD Model for Industrial Inspection Applications. 3DV 2013: 79-86 - 2012
- [c13]Li Guan, Ting Yu, Peter H. Tu, Ser-Nam Lim:
Simultaneous image segmentation and 3D plane fitting for RGB-D sensors - An iterative framework. CVPR Workshops 2012: 49-56 - 2011
- [c12]Ting Yu, Xiaoming Liu, Sernam Lim, Nils Krahnstoever, Peter H. Tu:
Automatic surveillance video matting using a shape prior. ICCV Workshops 2011: 1761-1768 - [c11]Ser-Nam Lim, Gianfranco Doretto, Jens Rittscher:
Multi-class Object Layout with Unsupervised Image Classification and Object Localization. ISVC (1) 2011: 573-585 - 2010
- [c10]Ming-Ching Chang, Nils Krahnstoever, Sernam Lim, Ting Yu:
Group Level Activity Recognition in Crowded Environments across Multiple Cameras. AVSS 2010: 56-63
2000 – 2009
- 2009
- [c9]Ting Yu, Ser-Nam Lim, Kedar A. Patwardhan, Nils Krahnstoever:
Monitoring, recognizing and discovering social networks. CVPR 2009: 1462-1469 - [p1]Nils Krahnstoever, Ting Yu, Ser-Nam Lim, Kedar A. Patwardhan:
Collaborative Control of Active Cameras in Large-Scale Surveillance. Multi-Camera Networks 2009: 165-188 - 2007
- [c8]Ser-Nam Lim, Larry S. Davis, Anurag Mittal:
Task Scheduling in Large Camera Networks. ACCV (1) 2007: 397-407 - [c7]Ser-Nam Lim, Larry S. Davis:
An Ease-of-Use Stereo-Based Particle Filter for Tracking Under Occlusion. Workshop on Human Motion 2007: 225-239 - 2006
- [b1]Ser-Nam Lim:
Sensor, Motion and Temporal Planning. University of Maryland, College Park, MD, USA, 2006 - [j1]Ser-Nam Lim, Larry S. Davis, Anurag Mittal:
Constructing task visibility intervals for video surveillance. Multim. Syst. 12(3): 211-226 (2006) - 2005
- [c6]Ser-Nam Lim, Anurag Mittal, Larry S. Davis, Nikos Paragios:
Fast Illumination-Invariant Background Subtraction Using Two Views: Error Analysis, Sensor Placement and Applications. CVPR (1) 2005: 1071-1078 - [c5]Ser-Nam Lim, Anurag Mittal, Larry Davis:
Constructing task visibility intervals for a surveillance system. VSSN@MM 2005: 141-148 - 2004
- [c4]Ser-Nam Lim, Anurag Mittal, Larry S. Davis, Nikos Paragios:
Uncalibrated stereo rectification for automatic 3d surveillance. ICIP 2004: 1357-1360 - [c3]Ali Zandifar, Ser-Nam Lim, Ramani Duraiswami, Nail A. Gumerov, Larry S. Davis:
Multi-level fast multipole method for thin plate spline evaluation. ICIP 2004: 1683-1686 - 2003
- [c2]Ser-Nam Lim, Larry S. Davis, Ahmed M. Elgammal:
A Scalable Image-Based Multi-Camera Visual Surveillance System. AVSS 2003: 205-212 - [c1]Ser-Nam Lim, Ahmed M. Elgammal, Larry S. Davis:
Image-based pan-tilt camera control in a multi-camera surveillance environment. ICME 2003: 645-648
Coauthor Index
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