SVDNet for Pedestrian Retrieval. - Yifan Sun 003; Liang Zheng 001; Weijian Deng; Shengjin Wang (ICCV, 2017)

A Word Embedding Transfer Model for Robust Text Categorization. - Yiming Zhang 011; Jing Wang 040; Weijian Deng; Yaojie Lu 001 (CCL, 2018)

Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification. - Weijian Deng; Liang Zheng 001; Qixiang Ye; Guoliang Kang; Yi Yang 001; Jianbin Jiao (CVPR, 2018)

Similarity-preserving Image-image Domain Adaptation for Person Re-identification. - Weijian Deng; Liang Zheng 001; Qixiang Ye; Yi Yang 001; Jianbin Jiao (CoRR, 2018)

Domain Alignment with Triplets. - Weijian Deng; Liang Zheng 001; Jianbin Jiao (CoRR, 2018)

Vehicle Re-Identification with Location and Time Stamps. - Kai Lv 002; Heming Du; Yunzhong Hou; Weijian Deng; Hao Sheng 001; Jianbin Jiao; Liang Zheng 001 (CVPR Workshops, 2019)

Are Labels Necessary for Classifier Accuracy Evaluation? - Weijian Deng; Liang Zheng 001 (CoRR, 2020)

Are Labels Always Necessary for Classifier Accuracy Evaluation? - Weijian Deng; Liang Zheng 001 (CVPR, 2021)

Ranking Models in Unlabeled New Environments. - Xiaoxiao Sun 002; Yunzhong Hou; Weijian Deng; Hongdong Li; Liang Zheng 001 (ICCV, 2021)

What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? - Weijian Deng; Stephen Gould; Liang Zheng 001 (ICML, 2021)

Rethinking Triplet Loss for Domain Adaptation. - Weijian Deng; Liang Zheng 001; Yifan Sun 003; Jianbin Jiao (IEEE Trans. Circuits Syst. Video Technol., 2021)

On the Strong Correlation Between Model Invariance and Generalization. - Weijian Deng; Stephen Gould; Liang Zheng 001 (NeurIPS, 2022)

Fine-Grained Classification via Categorical Memory Networks. - Weijian Deng; Joshua Marsh; Stephen Gould; Liang Zheng 001 (IEEE Trans. Image Process., 2022)

Reparameterized Residual Feature Network For Lightweight Image Super-Resolution. - Weijian Deng; Hongjie Yuan; Lunhui Deng; Zengtong Lu (CVPR Workshops, 2023)

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results. - Yawei Li 001; Yulun Zhang 001; Radu Timofte; Luc Van Gool; Lei Yu; Youwei Li; Xinpeng Li 002; Ting Jiang; Qi Wu 017; Mingyan Han; Wenjie Lin; Chengzhi Jiang; et al. (CVPR Workshops, 2023)

A Bag-of-Prototypes Representation for Dataset-Level Applications. - Weijie Tu; Weijian Deng; Tom Gedeon; Liang Zheng 001 (CVPR, 2023)

Adaptive Calibrator Ensemble: Navigating Test Set Difficulty in Out-of-Distribution Scenarios. - Yuli Zou; Weijian Deng; Liang Zheng 001 (ICCV, 2023)

Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation. - Weijian Deng; Yumin Suh; Stephen Gould; Liang Zheng 001 (ICML, 2023)

A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP). - Weijie Tu; Weijian Deng; Tom Gedeon (NeurIPS, 2023)

Split to Learn: Gradient Split for Multi-Task Human Image Analysis. - Weijian Deng; Yumin Suh; Xiang Yu 002; Masoud Faraki; Liang Zheng 001; Manmohan Chandraker (WACV, 2023)

Confidence and Dispersity Speak: Characterising Prediction Matrix for Unsupervised Accuracy Estimation. - Weijian Deng; Yumin Suh; Stephen Gould; Liang Zheng 001 (CoRR, 2023)

Adaptive Calibrator Ensemble for Model Calibration under Distribution Shift. - Yuli Zou; Weijian Deng; Liang Zheng 001 (CoRR, 2023)

Differentiable Neural Surface Refinement for Modeling Transparent Objects. - Weijian Deng; Dylan Campbell; Chunyi Sun; Shubham Kanitkar; Matthew E. Shaffer; Stephen Gould (CVPR, 2024)

UNAD: Universal Anatomy-Initialized Noise Distribution Learning Framework Towards Low-Dose CT Denoising. - Lingrui Gu; Weijian Deng; Guoli Wang (ICASSP, 2024)

An Empirical Study Into What Matters for Calibrating Vision-Language Models. - Weijie Tu; Weijian Deng; Dylan Campbell; Stephen Gould; Tom Gedeon (ICML, 2024)

MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts. - Renchunzi Xie; Ambroise Odonnat; Vasilii Feofanov; Weijian Deng; Jianfeng Zhang; Bo An 001 (NeurIPS, 2024)

Ray Deformation Networks for Novel View Synthesis of Refractive Objects. - Weijian Deng; Dylan Campbell; Chunyi Sun; Shubham Kanitkar; Matthew E. Shaffer; Stephen Gould (WACV, 2024)

Manual-PA: Learning 3D Part Assembly from Instruction Diagrams. - Jiahao Zhang; Anoop Cherian; Cristian Rodriguez; Weijian Deng; Stephen Gould (CoRR, 2024)

Ranked from Within: Ranking Large Multimodal Models for Visual Question Answering Without Labels. - Weijie Tu; Weijian Deng; Dylan Campbell; Yu Yao 005; Jiyang Zheng; Tom Gedeon; Tongliang Liu (CoRR, 2024)

What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions? - Weijie Tu; Weijian Deng; Liang Zheng 001; Tom Gedeon (Trans. Mach. Learn. Res., 2024)

AutoEval: Are Labels Always Necessary for Classifier Accuracy Evaluation? - Weijian Deng; Liang Zheng 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

3D-GPT: Procedural 3D Modeling with Large Language Models. - Chunyi Sun; Junlin Han; Weijian Deng; Xinlong Wang; Zishan Qin; Stephen Gould (3DV, 2025)

Pos3R: 6D Pose Estimation for Unseen Objects Made Easy. - Weijian Deng; Dylan Campbell; Chunyi Sun; Jiahao Zhang; Shubham Kanitkar; Matthew E. Shaffer; Stephen Gould (CVPR, 2025)

Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions. - ZiYi Dong; Chengxing Zhou; Weijian Deng; Pengxu Wei; Xiangyang Ji; Liang Lin (CoRR, 2025)

RefRef: A Synthetic Dataset and Benchmark for Reconstructing Refractive and Reflective Objects. - Yue Yin; Enze Tao; Weijian Deng; Dylan Campbell (CoRR, 2025)

Probe by Gaming: A Game-based Benchmark for Assessing Conceptual Knowledge in LLMs. - Shuhang Xu; Weijian Deng; Yixuan Zhou; Fangwei Zhong (CoRR, 2025)

Toward a Holistic Evaluation of Robustness in CLIP Models. - Weijie Tu; Weijian Deng; Tom Gedeon (IEEE Trans. Pattern Anal. Mach. Intell., 2025)