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Weijian Deng
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2020 – today
- 2024
- [j4]Weijian Deng
, Liang Zheng
AutoEval: Are Labels Always Necessary for Classifier Accuracy Evaluation? IEEE Trans. Pattern Anal. Mach. Intell. 46(3): 1868-1880 (2024) - [j3]Weijie Tu, Weijian Deng, Liang Zheng, Tom Gedeon:
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions? Trans. Mach. Learn. Res. 2024 (2024) - [c19]Weijian Deng, Dylan Campbell, Chunyi Sun, Shubham Kanitkar, Matthew E. Shaffer, Stephen Gould:
Differentiable Neural Surface Refinement for Modeling Transparent Objects. CVPR 2024: 20268-20277 - [c18]Lingrui Gu, Weijian Deng, Guoli Wang:
UNAD: Universal Anatomy-Initialized Noise Distribution Learning Framework Towards Low-Dose CT Denoising. ICASSP 2024: 1671-1675 - [c17]Weijie Tu, Weijian Deng, Dylan Campbell, Stephen Gould, Tom Gedeon:
An Empirical Study Into What Matters for Calibrating Vision-Language Models. ICML 2024 - [c16]Weijian Deng, Dylan Campbell
Ray Deformation Networks for Novel View Synthesis of Refractive Objects. WACV 2024: 3106-3116 - [i18]Weijie Tu, Weijian Deng, Tom Gedeon:
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP). CoRR abs/2402.07410 (2024) - [i17]Weijie Tu, Weijian Deng, Dylan Campbell, Stephen Gould, Tom Gedeon:
An Empirical Study Into What Matters for Calibrating Vision-Language Models. CoRR abs/2402.07417 (2024) - [i16]Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Weijian Deng, Jianfeng Zhang, Bo An:
MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts. CoRR abs/2405.18979 (2024) - [i15]Weijie Tu, Weijian Deng, Liang Zheng, Tom Gedeon:
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions? CoRR abs/2406.09908 (2024) - [i14]Weijie Tu, Weijian Deng, Tom Gedeon:
Toward a Holistic Evaluation of Robustness in CLIP Models. CoRR abs/2410.01534 (2024) - 2023
- [c15]Weijian Deng, Hongjie Yuan, Lunhui Deng, Zengtong Lu:
Reparameterized Residual Feature Network For Lightweight Image Super-Resolution. CVPR Workshops 2023: 1712-1721 - [c14]Yawei Li, Yulun Zhang, Radu Timofte, Luc Van Gool, Lei Yu, Youwei Li, Xinpeng Li, Ting Jiang, Qi Wu, Mingyan Han, Wenjie Lin, Chengzhi Jiang, Jinting Luo, Haoqiang Fan, Shuaicheng Liu, Yucong Wang, Minjie Cai, Mingxi Li, Yuhang Zhang, Xianjun Fan, Yankai Sheng, Yanyu Mao, Nihao Zhang, Qian Wang, Mingjun Zheng, Long Sun, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Zhongbao Yang, Yan Wang, Erlin Pan, Qixuan Cai, Xinan Dai, Magauiya Zhussip, Nikolay Kalyazin, Dmitry Vyal, Xueyi Zou, Youliang Yan, Heaseo Chung, Jin Zhang, Gaocheng Yu, Feng Zhang, Hongbin Wang, Bohao Liao, Zhibo Du, Yu-Liang Wu, Gege Shi, Long Peng, Yang Wang, Yang Cao, Zhengjun Zha, Zhi-Kai Huang, Yi-Chung Chen, Yuan-Chun Chiang, Hao-Hsiang Yang, Wei-Ting Chen, Hua-En Chang, I-Hsiang Chen, Chia-Hsuan Hsieh, Sy-Yen Kuo, Xin Liu, Jiahao Pan, Hongyuan Yu, Weichen Yu, Lin Ge, Jiahua Dong, Yajun Zou, Zhuoyuan Wu, Binnan Han, Xiaolin Zhang, Heng Zhang, Xuanwu Yin, Kunlong Zuo, Weijian Deng, Hongjie Yuan, Zengtong Lu, Mingyu Ouyang, Wenzhuo Ma, Nian Liu, Hanyou Zheng, Yuantong Zhang, Junxi Zhang, Zhenzhong Chen, Garas Gendy, Nabil Sabor, Jingchao Hou, Guanghui He, Yurui Zhu, Xi Wang, Xueyang Fu, Zheng-Jun Zha, Daheng Yin, Mengyang Liu, Baijun Chen, Ao Li, Lei Luo, Kangjun Jin, Ce Zhu, Xiaoming Zhang, Chengxing Xie, Linze Li, Haiteng Meng, Tianlin Zhang, Tianrui Li, Xiaole Zhao, Zhao Zhang, Baiang Li, Huan Zheng, Suiyi Zhao, Yangcheng Gao, Jiahuan Ren, Kang Hu, Jingpeng Shi, Zhijian Wu, Dingjiang Huang, Jinchen Zhu, Hui Li, Qianru Xv, Tianle Liu, Gang Wu, Junpeng Jiang, Xianming Liu, Junjun Jiang, Mingjian Zhang, Shizhuang Weng, Jing Hu, Chengxu Wu, Qinrui Fan, Chengming Feng, Ziwei Luo, Shu Hu, Siwei Lyu, Xi Wu, Xin Wang:
NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results. CVPR Workshops 2023: 1922-1960 - [c13]Weijie Tu, Weijian Deng, Tom Gedeon, Liang Zheng:
A Bag-of-Prototypes Representation for Dataset-Level Applications. CVPR 2023: 2881-2892 - [c12]Yuli Zou, Weijian Deng, Liang Zheng:
Adaptive Calibrator Ensemble: Navigating Test Set Difficulty in Out-of-Distribution Scenarios. ICCV 2023: 19276-19285 - [c11]Weijian Deng, Yumin Suh, Stephen Gould, Liang Zheng:
Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation. ICML 2023: 7658-7674 - [c10]Weijie Tu, Weijian Deng, Tom Gedeon:
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP). NeurIPS 2023 - [c9]Weijian Deng, Yumin Suh, Xiang Yu, Masoud Faraki, Liang Zheng
Split to Learn: Gradient Split for Multi-Task Human Image Analysis. WACV 2023: 4340-4349 - [i13]Weijian Deng, Yumin Suh, Stephen Gould, Liang Zheng:
Confidence and Dispersity Speak: Characterising Prediction Matrix for Unsupervised Accuracy Estimation. CoRR abs/2302.01094 (2023) - [i12]Yuli Zou, Weijian Deng, Liang Zheng:
Adaptive Calibrator Ensemble for Model Calibration under Distribution Shift. CoRR abs/2303.05331 (2023) - [i11]Weijie Tu, Weijian Deng, Tom Gedeon, Liang Zheng:
A Bag-of-Prototypes Representation for Dataset-Level Applications. CoRR abs/2303.13251 (2023) - [i10]Chunyi Sun, Junlin Han, Weijian Deng, Xinlong Wang, Zishan Qin, Stephen Gould:
3D-GPT: Procedural 3D Modeling with Large Language Models. CoRR abs/2310.12945 (2023) - 2022
- [j2]Weijian Deng
Fine-Grained Classification via Categorical Memory Networks. IEEE Trans. Image Process. 31: 4186-4196 (2022) - [c8]Weijian Deng, Stephen Gould, Liang Zheng:
On the Strong Correlation Between Model Invariance and Generalization. NeurIPS 2022 - [i9]Weijian Deng, Stephen Gould, Liang Zheng:
On the Strong Correlation Between Model Invariance and Generalization. CoRR abs/2207.07065 (2022) - 2021
- [j1]Weijian Deng
Rethinking Triplet Loss for Domain Adaptation. IEEE Trans. Circuits Syst. Video Technol. 31(1): 29-37 (2021) - [c7]Weijian Deng, Liang Zheng
Are Labels Always Necessary for Classifier Accuracy Evaluation? CVPR 2021: 15069-15078 - [c6]Xiaoxiao Sun, Yunzhong Hou
Ranking Models in Unlabeled New Environments. ICCV 2021: 11741-11751 - [c5]Weijian Deng, Stephen Gould, Liang Zheng
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? ICML 2021: 2579-2589 - [i8]Weijian Deng, Stephen Gould, Liang Zheng:
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? CoRR abs/2106.05961 (2021) - [i7]Xiaoxiao Sun, Yunzhong Hou, Weijian Deng, Hongdong Li, Liang Zheng:
Ranking Models in Unlabeled New Environments. CoRR abs/2108.10310 (2021) - 2020
- [i6]Weijian Deng
Are Labels Necessary for Classifier Accuracy Evaluation? CoRR abs/2007.02915 (2020) - [i5]Weijian Deng
Fine-grained Classification via Categorical Memory Networks. CoRR abs/2012.06793 (2020)
2010 – 2019
- 2019
- [c4]Kai Lv, Heming Du, Yunzhong Hou, Weijian Deng, Hao Sheng, Jianbin Jiao, Liang Zheng:
Vehicle Re-Identification with Location and Time Stamps. CVPR Workshops 2019: 399-406 - 2018
- [c3]Yiming Zhang
A Word Embedding Transfer Model for Robust Text Categorization. CCL 2018: 314-323 - [c2]Weijian Deng, Liang Zheng
Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification. CVPR 2018: 994-1003 - [i4]Weijian Deng
Similarity-preserving Image-image Domain Adaptation for Person Re-identification. CoRR abs/1811.10551 (2018) - [i3]Weijian Deng, Liang Zheng, Jianbin Jiao:
Domain Alignment with Triplets. CoRR abs/1812.00893 (2018) - 2017
- [c1]Yifan Sun, Liang Zheng
SVDNet for Pedestrian Retrieval. ICCV 2017: 3820-3828 - [i2]Yifan Sun, Liang Zheng, Weijian Deng, Shengjin Wang:
SVDNet for Pedestrian Retrieval. CoRR abs/1703.05693 (2017) - [i1]Weijian Deng, Liang Zheng, Guoliang Kang, Yi Yang, Qixiang Ye, Jianbin Jiao:
Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification. CoRR abs/1711.07027 (2017)
Coauthor Index
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