25 citations · 34 across the 7 of their papers we have counts for
7 papers
TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing
Peizhen Zhang, Yang Li, Xunsong Li +10
Modern image generation model rapidly grows their sizes to meet high-fidelity image synthesis. However, they gradually become unaffordable for their enormous parameter consumption…
Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation
Xiao He, Yang Li, Peizhen Zhang +3
Diffusion models exhibit remarkable generative capability, but their high latency limits practical deployment. Many studies have attempted to reduce sampling steps to accelerate in…
Relieving Long-tailed Instance Segmentation via Pairwise Class Balance
Yin-Yin He, Peizhen Zhang, Xiu-Shen Wei +2
Long-tailed instance segmentation is a challenging task due to the extreme imbalance of training samples among classes. It causes severe biases of the head classes (with majority s…
Instance-Conditional Knowledge Distillation for Object Detection
Zijian Kang, Peizhen Zhang, Xiangyu Zhang +2
Knowledge distillation has shown great success in classification, however, it is still challenging for detection. In a typical image for detection, representations from different l…
LGD: Label-guided Self-distillation for Object Detection
Peizhen Zhang, Zijian Kang, Tong Yang +3
In this paper, we propose the first self-distillation framework for general object detection, termed LGD (Label-Guided self-Distillation). Previous studies rely on a strong pretrai…
Dynamic Scale Training for Object Detection
Yukang Chen, Peizhen Zhang, Zeming Li +5
We propose a Dynamic Scale Training paradigm (abbreviated as DST) to mitigate scale variation challenge in object detection. Previous strategies like image pyramid, multi-scale tra…
Latent Embeddings for Collective Activity Recognition
Yongyi Tang, Peizhen Zhang, Jian-Fang Hu +1
Rather than simply recognizing the action of a person individually, collective activity recognition aims to find out what a group of people is acting in a collective scene. Previ-…