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◀ ▷ joint publications with coauthor community group 1
Publications
- 2024
[j8]Mahyar Abbasian
, Elahe Khatibi, Iman Azimi, David Oniani, Zahra Shakeri Hossein Abad, Alexander Thieme, Ram Sriram, Zhongqi Yang, Yanshan Wang, Bryant Lin, Olivier Gevaert, Li-Jia Li, Ramesh C. Jain, Amir M. Rahmani:
Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI. npj Digit. Medicine 7(1) (2024)- 2023
- [j7]Sophie Ostmeier, Brian Axelrod, Fabian Isensee, Jeroen Bertels, Michael Mlynash, Soren Christensen, Maarten G. Lansberg, Gregory W. Albers, Rajen Sheth, Benjamin F. J. Verhaaren, Abdelkader Mahammedi, Li-Jia Li, Greg Zaharchuk, Jeremy J. Heit:
USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging. Medical Image Anal. 90: 102927 (2023) - [i23]Mahyar Abbasian, Elahe Khatibi, Iman Azimi, David Oniani, Zahra Shakeri Hossein Abad, Alexander Thieme, Zhongqi Yang, Yanshan Wang, Bryant Lin, Olivier Gevaert, Li-Jia Li, Ramesh C. Jain, Amir M. Rahmani:
Foundation Metrics: Quantifying Effectiveness of Healthcare Conversations powered by Generative AI. CoRR abs/2309.12444 (2023) - 2022
- [i22]Zhanpeng Feng, Shiliang Zhang, Rinyoichi Takezoe, Wenze Hu, Manmohan Chandraker, Li-Jia Li, Vijay K. Narayanan, Xiaoyu Wang:
ALBench: A Framework for Evaluating Active Learning in Object Detection. CoRR abs/2207.13339 (2022) - [i21]Sophie Ostmeier, Brian Axelrod, Jeroen Bertels, Fabian Isensee, Maarten G. Lansberg, Soren Christensen, Gregory W. Albers, Li-Jia Li, Jeremy J. Heit:
Evaluation of Medical Image Segmentation Models for Uncertain, Small or Empty Reference Annotations. CoRR abs/2209.13008 (2022) - [i20]Sophie Ostmeier, Jeremy J. Heit, Brian Axelrod, Li-Jia Li, Greg Zaharchuk, Benjamin F. J. Verhaaren, Abdelkader Mahammedi, Soren Christensen, Maarten G. Lansberg:
Non-inferiority of Deep Learning Model to Segment Acute Stroke on Non-contrast CT Compared to Neuroradiologists. CoRR abs/2211.15341 (2022) - 2021
- [i19]Phoenix X. Huang, Wenze Hu, William Brendel, Manmohan Chandraker, Li-Jia Li, Xiaoyu Wang:
YMIR: A Rapid Data-centric Development Platform for Vision Applications. CoRR abs/2111.10046 (2021) - 2019
- [j6]Junwei Liang, Lu Jiang, Liangliang Cao, Yannis Kalantidis, Li-Jia Li, Alexander G. Hauptmann:
Focal Visual-Text Attention for Memex Question Answering. IEEE Trans. Pattern Anal. Mach. Intell. 41(8): 1893-1908 (2019) - [c40]Nam Vo, Lu Jiang, Chen Sun, Kevin Murphy, Li-Jia Li, Li Fei-Fei, James Hays:
Composing Text and Image for Image Retrieval - an Empirical Odyssey. CVPR 2019: 6439-6448 - [c39]Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li:
Generative Modeling for Small-Data Object Detection. ICCV 2019: 6072-6080 - [c38]Jiyang Gao, Jiang Wang, Shengyang Dai, Li-Jia Li, Ram Nevatia:
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection. ICCV 2019: 9507-9516 - [c37]Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, Li Fei-Fei:
Eidetic 3D LSTM: A Model for Video Prediction and Beyond. ICLR (Poster) 2019 - [p3]Zhe Li, Chong Wang, Mei Han, Yuan Xue, Wei Wei, Li-Jia Li, Li Fei-Fei:
Thoracic Disease Identification and Localization with Limited Supervision. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics 2019: 139-161 - [i18]Alejandro Newell, Lu Jiang, Chong Wang, Li-Jia Li, Jia Deng:
Feature Partitioning for Efficient Multi-Task Architectures. CoRR abs/1908.04339 (2019) - [i17]Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li:
Generative Modeling for Small-Data Object Detection. CoRR abs/1910.07169 (2019) - 2018
- [c36]Junwei Liang, Lu Jiang, Liangliang Cao, Li-Jia Li, Alexander G. Hauptmann:
Focal Visual-Text Attention for Visual Question Answering. CVPR 2018: 6135-6143 - [c35]Xinlei Chen, Li-Jia Li, Li Fei-Fei, Abhinav Gupta:
Iterative Visual Reasoning Beyond Convolutions. CVPR 2018: 7239-7248 - [c34]Zhe Li, Chong Wang, Mei Han, Yuan Xue, Wei Wei, Li-Jia Li, Li Fei-Fei:
Thoracic Disease Identification and Localization With Limited Supervision. CVPR 2018: 8290-8299 - [c33]Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan L. Yuille, Jonathan Huang, Kevin Murphy:
Progressive Neural Architecture Search. ECCV (1) 2018: 19-35 - [c32]Yihui He, Ji Lin, Zhijian Liu, Hanrui Wang, Li-Jia Li, Song Han:
AMC: AutoML for Model Compression and Acceleration on Mobile Devices. ECCV (7) 2018: 815-832 - [c31]Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-Fei:
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels. ICML 2018: 2309-2318 - [c30]Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos, Peter W. Glynn, Yinyu Ye, Li-Jia Li, Li Fei-Fei:
Distributed Asynchronous Optimization with Unbounded Delays: How Slow Can You Go? ICML 2018: 5965-5974 - [i16]Kiran Koshy Thekumparampil, Chong Wang, Sewoong Oh, Li-Jia Li:
Attention-based Graph Neural Network for Semi-supervised Learning. CoRR abs/1803.03735 (2018) - [i15]Xinlei Chen, Li-Jia Li, Li Fei-Fei, Abhinav Gupta:
Iterative Visual Reasoning Beyond Convolutions. CoRR abs/1803.11189 (2018) - [i14]Junwei Liang, Lu Jiang, Liangliang Cao, Li-Jia Li, Alexander G. Hauptmann:
Focal Visual-Text Attention for Visual Question Answering. CoRR abs/1806.01873 (2018) - [i13]Jiyang Gao, Jiang Wang, Shengyang Dai, Li-Jia Li, Ram Nevatia:
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection. CoRR abs/1812.00124 (2018) - [i12]David Xue, Anin Sayana, Evan Darke, Kelly Shen, Jun-Ting Hsieh, Zelun Luo, Li-Jia Li, N. Lance Downing, Arnold Milstein, Li Fei-Fei:
Vision-Based Gait Analysis for Senior Care. CoRR abs/1812.00169 (2018) - [i11]Nam Vo, Lu Jiang, Chen Sun, Kevin Murphy, Li-Jia Li, Li Fei-Fei, James Hays:
Composing Text and Image for Image Retrieval - An Empirical Odyssey. CoRR abs/1812.07119 (2018) - 2017
- [j5]Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, Li Fei-Fei:
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations. Int. J. Comput. Vis. 123(1): 32-73 (2017) - [c29]Zhou Ren, Xiaoyu Wang, Ning Zhang, Xutao Lv, Li-Jia Li:
Deep Reinforcement Learning-Based Image Captioning with Embedding Reward. CVPR 2017: 1151-1159 - [c28]Linjie Yang, Kevin D. Tang, Jianchao Yang, Li-Jia Li:
Dense Captioning with Joint Inference and Visual Context. CVPR 2017: 1978-1987 - [c27]Yuncheng Li, Jianchao Yang, Yale Song, Liangliang Cao, Jiebo Luo, Li-Jia Li:
Learning from Noisy Labels with Distillation. ICCV 2017: 1928-1936 - [c26]Jinxi Guo, Ning Xu, Li-Jia Li, Abeer Alwan:
Attention Based CLDNNs for Short-Duration Acoustic Scene Classification. INTERSPEECH 2017: 469-473 - [c25]Carl Yang, Lin Zhong, Li-Jia Li, Luo Jie:
Bi-directional Joint Inference for User Links and Attributes on Large Social Graphs. WWW (Companion Volume) 2017: 564-573 - [e1]Qiong Liu, Rainer Lienhart, Haohong Wang, Sheng-Wei "Kuan-Ta" Chen, Susanne Boll, Yi-Ping Phoebe Chen, Gerald Friedland, Jia Li, Shuicheng Yan:
Proceedings of the 2017 ACM on Multimedia Conference, MM 2017, Mountain View, CA, USA, October 23-27, 2017. ACM 2017, ISBN 978-1-4503-4906-2 [contents] - [i10]Zhou Ren, Xiaoyu Wang, Ning Zhang, Xutao Lv, Li-Jia Li:
Deep Reinforcement Learning-based Image Captioning with Embedding Reward. CoRR abs/1704.03899 (2017) - [i9]Zhe Li, Chong Wang, Mei Han, Yuan Xue, Wei Wei, Li-Jia Li, Li Fei-Fei:
Thoracic Disease Identification and Localization with Limited Supervision. CoRR abs/1711.06373 (2017) - [i8]Chenxi Liu, Barret Zoph, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan L. Yuille, Jonathan Huang, Kevin Murphy:
Progressive Neural Architecture Search. CoRR abs/1712.00559 (2017) - [i7]Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, Li Fei-Fei:
MentorNet: Regularizing Very Deep Neural Networks on Corrupted Labels. CoRR abs/1712.05055 (2017) - 2016
- [j4]Bart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, Li-Jia Li:
YFCC100M: the new data in multimedia research. Commun. ACM 59(2): 64-73 (2016) - [c24]Mohammad Moghimi, Serge J. Belongie, Mohammad J. Saberian, Jian Yang, Nuno Vasconcelos, Li-Jia Li:
Boosted Convolutional Neural Networks. BMVC 2016 - [c23]David A. Shamma, Lyndon Kennedy, Li-Jia Li, Bart Thomee, Haojian Jin, Jeff Yuan:
Finding Weather Photos: Community-Supervised Methods for Editorial Curation of Online Sources. CSCW 2016: 86-96 - [p2]Li-Jia Li, Rahul Kumar Jha, Bart Thomee, David Ayman Shamma, Liangliang Cao, Yang Wang:
Where the Photos Were Taken: Location Prediction by Learning from Flickr Photos. Large-Scale Visual Geo-Localization 2016: 41-58 - [i6]Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A. Shamma, Michael S. Bernstein, Li Fei-Fei:
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations. CoRR abs/1602.07332 (2016) - [i5]Linjie Yang, Kevin D. Tang, Jianchao Yang, Li-Jia Li:
Dense Captioning with Joint Inference and Visual Context. CoRR abs/1611.06949 (2016) - 2015
- [j3]Li-Jia Li, David A. Shamma, Xiangnan Kong, Sina Jafarpour, Roelof van Zwol, Xuanhui Wang:
CelebrityNet: A Social Network Constructed from Large-Scale Online Celebrity Images. ACM Trans. Multim. Comput. Commun. Appl. 12(1): 3:1-3:22 (2015) - [c22]Olga Russakovsky, Li-Jia Li, Li Fei-Fei:
Best of both worlds: Human-machine collaboration for object annotation. CVPR 2015: 2121-2131 - [c21]Justin Johnson, Ranjay Krishna, Michael Stark, Li-Jia Li, David A. Shamma, Michael S. Bernstein, Li Fei-Fei:
Image retrieval using scene graphs. CVPR 2015: 3668-3678 - [c20]Sachin Sudhakar Farfade, Mohammad J. Saberian, Li-Jia Li:
Multi-view Face Detection Using Deep Convolutional Neural Networks. ICMR 2015: 643-650 - [c19]Shih-Fu Chang, Matthew Cooper, Denver Dash, Funda Kivran-Swaine, Jia Li, David A. Shamma:
Opportunities and Challenges of Industry-Academic Collaborations in Multimedia Research. ACM Multimedia 2015: 45 - [i4]Sachin Sudhakar Farfade, Mohammad J. Saberian, Li-Jia Li:
Multi-view Face Detection Using Deep Convolutional Neural Networks. CoRR abs/1502.02766 (2015) - [i3]Bart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, Li-Jia Li:
The New Data and New Challenges in Multimedia Research. CoRR abs/1503.01817 (2015) - 2014
- [j2]Li-Jia Li, Hao Su, Yongwhan Lim, Li Fei-Fei:
Object Bank: An Object-Level Image Representation for High-Level Visual Recognition. Int. J. Comput. Vis. 107(1): 20-39 (2014) - [c18]Kevin D. Tang, Armand Joulin, Li-Jia Li, Li Fei-Fei:
Co-localization in Real-World Images. CVPR 2014: 1464-1471 - [c16]Jonathan Krause, Timnit Gebru, Jia Deng, Li-Jia Li, Li Fei-Fei:
Learning Features and Parts for Fine-Grained Recognition. ICPR 2014: 26-33 - [c15]Li-Jia Li, Xiangnan Kong, Philip S. Yu:
Visual Recognition by Exploiting Latent Social Links in Image Collections. MMM (1) 2014: 121-132 - [c14]Xiangnan Kong, Zhaoming Wu, Li-Jia Li, Ruofei Zhang, Philip S. Yu, Hang Wu, Wei Fan:
Large-Scale Multi-Label Learning with Incomplete Label Assignments. SDM 2014: 920-928 - [c13]Somayah Albaradei, Yang Wang, Liangliang Cao, Li-Jia Li:
Learning mid-level features from object hierarchy for image classification. WACV 2014: 235-240 - [i2]Xiangnan Kong, Zhaoming Wu, Li-Jia Li, Ruofei Zhang, Philip S. Yu, Hang Wu, Wei Fan:
Large-Scale Multi-Label Learning with Incomplete Label Assignments. CoRR abs/1407.1538 (2014) - [i1]Can Xu, Suleyman Cetintas, Kuang-Chih Lee, Li-Jia Li:
Visual Sentiment Prediction with Deep Convolutional Neural Networks. CoRR abs/1411.5731 (2014) - 2013
- [c12]Yannis Kalantidis, Lyndon Kennedy, Li-Jia Li:
Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos. ICMR 2013: 105-112 - 2012
- [c11]Li-Jia Li, Jun Zhu, Hao Su, Eric P. Xing, Li Fei-Fei:
Multi-Level Structured Image Coding on High-Dimensional Image Representation. ACCV (2) 2012: 147-161 - [c10]Sina Jafarpour, Li-Jia Li, Roelof van Zwol:
Digital Paparazzi: Spotting Celebrities in Professional Photo Libraries. ACCV (2) 2012: 694-707 - 2010
- [j1]Li-Jia Li, Li Fei-Fei:
OPTIMOL: Automatic Online Picture Collection via Incremental Model Learning. Int. J. Comput. Vis. 88(2): 147-168 (2010) - [c9]Li-Jia Li, Chong Wang, Yongwhan Lim, David M. Blei, Li Fei-Fei:
Building and using a semantivisual image hierarchy. CVPR 2010: 3336-3343 - [c8]Li-Jia Li, Hao Su, Yongwhan Lim, Li Fei-Fei:
Objects as Attributes for Scene Classification. ECCV Workshops (1) 2010: 57-69 - [c7]Li-Jia Li, Hao Su, Eric P. Xing, Li Fei-Fei:
Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification. NIPS 2010: 1378-1386 - [c6]Jun Zhu, Li-Jia Li, Li Fei-Fei, Eric P. Xing:
Large Margin Learning of Upstream Scene Understanding Models. NIPS 2010: 2586-2594 - [p1]Li Fei-Fei, Li-Jia Li:
What, Where and Who? Telling the Story of an Image by Activity Classification, Scene Recognition and Object Categorization. Computer Vision: Detection, Recognition and Reconstruction 2010: 157-171 - 2009
- [c5]Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, Li Fei-Fei:
ImageNet: A large-scale hierarchical image database. CVPR 2009: 248-255 - [c4]Li-Jia Li, Richard Socher, Li Fei-Fei:
Towards total scene understanding: Classification, annotation and segmentation in an automatic framework. CVPR 2009: 2036-2043 - 2007
- [c3]Li-Jia Li, Juan Carlos Niebles, Li Fei-Fei:
OPTIMOL: A Framework for Online Picture Collection via Incremental Model Learning. AAAI 2007: 1987-1988 - [c2]Li-Jia Li, Gang Wang, Li Fei-Fei:
OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning. CVPR 2007 - [c1]Li-Jia Li, Li Fei-Fei:
What, where and who? Classifying events by scene and object recognition. ICCV 2007: 1-8
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last updated on 2024-09-25 01:40 CEST by the dblp team
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