1 citations · 2 across the 7 of their papers we have counts for
7 papers
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li +5
Knowledge distillation (KD) is a promising yet challenging model compression technique that transfers rich learning representations from a well-performing but cumbersome teacher mo…
Enhanced Bayesian Personalized Ranking for Robust Hard Negative Sampling in Recommender Systems
Kexin Shi, Jing Zhang, Linjiajie Fang +2
In implicit collaborative filtering, hard negative mining techniques are developed to accelerate and enhance the recommendation model learning. However, the inadvertent selection o…
AiOS: All-in-One-Stage Expressive Human Pose and Shape Estimation
Qingping Sun, Yanjun Wang, Ailing Zeng +8
Expressive human pose and shape estimation (a.k.a. 3D whole-body mesh recovery) involves the human body, hand, and expression estimation. Most existing methods have tackled this ta…
CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation
Jun Wang, Haoxuan Li, Chi Zhang +4
Recommender systems are designed to learn user preferences from observed feedback and comprise many fundamental tasks, such as rating prediction and post-click conversion rate (pCV…
Elucidating The Design Space of Classifier-Guided Diffusion Generation
Jiajun Ma, Tianyang Hu, Wenjia Wang +1
Guidance in conditional diffusion generation is of great importance for sample quality and controllability. However, existing guidance schemes are to be desired. On one hand, mains…
Learning Dense UV Completion for Human Mesh Recovery
Yanjun Wang, Qingping Sun, Wenjia Wang +4
Human mesh reconstruction from a single image is challenging in the presence of occlusion, which can be caused by self, objects, or other humans. Existing methods either fail to se…