Structure and appearance preserving network flow for multi-object tracking. - Shi Pu 002; Honggang Zhang 002; Kaili Zhao (ICPR, 2016)

Deep Attentive Tracking via Reciprocative Learning. - Shi Pu 002; Yibing Song; Chao Ma 004; Honggang Zhang 002; Ming-Hsuan Yang 001 (NeurIPS, 2018)

Enhanced Initialization with Multi-Stage Learning for Robust Visual Tracking. - Jin Feng; Shi Pu 002; Kaili Zhao; Honggang Zhang 002; Tianming Du (VCIP, 2019)

Learning Objectness Transfer Networks for Visual Tracking. - Shi Pu 002; Kaili Zhao; Honggang Zhang 002 (IEEE Access, 2019)

Robust visual tracking by embedding combination and weighted-gradient optimization. - Jin Feng; Peng Xu; Shi Pu 002; Kaili Zhao; Honggang Zhang 002 (Pattern Recognit., 2020)

Learning Recurrent Memory Activation Networks for Visual Tracking. - Shi Pu 002; Yibing Song; Chao Ma 004; Honggang Zhang 002; Ming-Hsuan Yang 001 (IEEE Trans. Image Process., 2021)

One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. - Fan Bao; Shen Nie; Kaiwen Xue; Chongxuan Li; Shi Pu 002; Yaole Wang; Gang Yue; Yue Cao; Hang Su 006; Jun Zhu 001 (ICML, 2023)

Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning. - Shengfang Zhai; Yinpeng Dong; Qingni Shen; Shi Pu 002; Yuejian Fang; Hang Su 006 (ACM Multimedia, 2023)