7 citations · 7 across the 5 of their papers we have counts for
8 papers · 1 filter
CtrlCache: Accelerating Interactive Video World Models with Control-Aware Caching
Shangye Song, Dong Gong, Hong Jia +2
Interactive video world models need to generate each video chunk efficiently while responding faithfully to user controls. Many systems use chunk-wise autoregressive generation wit…
Generating the Wild: Individual-Consistent Image-to-Video Generation for Wildlife
Yuzhuo Li, Di Zhao, Xinyu Zhang +2
Individual-level wildlife identification often suffers from data scarcity, as varying observations of the same animal under diverse poses, viewpoints, and motions are rarely availa…
Advancing Wildlife Conservation through Multimodal Animal Re-Identification with Environmental Metadata
Yuzhuo Li, Di Zhao, Tingrui Qiao +3
Identifying individual animals is crucial for effective wildlife monitoring and conservation efforts. Recent advancements in computer vision have shown promise in animal re-identif…
Let Your Image Move with Your Motion! -- Implicit Multi-Object Multi-Motion Transfer
Yuze Li, Dong Gong, Xiao Cao +6
Motion transfer has emerged as a promising direction for controllable video generation, yet existing methods largely focus on single-object scenarios and struggle when multiple obj…
Animal Re-Identification on Microcontrollers
Yubo Chen, Di Zhao, Yun Sing Koh +1
Camera-based animal re-identification (Animal Re-ID) can support wildlife monitoring and precision livestock management in large outdoor environments with limited wireless connecti…
Model-agnostic Adversarial Attack and Defense for Vision-Language-Action Models
Haochuan Xu, Yun Sing Koh, Shuhuai Huang +4
Vision-Language-Action (VLA) models have achieved revolutionary progress in robot learning, enabling robots to execute complex physical robot tasks from natural language instructio…
MetaWild: A Multimodal Dataset for Animal Re-Identification with Environmental Metadata
Yuzhuo Li, Di Zhao, Tingrui Qiao +3
Identifying individual animals within large wildlife populations is essential for effective wildlife monitoring and conservation efforts. Recent advancements in computer vision hav…
An Individual Identity-Driven Framework for Animal Re-Identification
Yihao Wu, Di Zhao, Jingfeng Zhang +1
Reliable re-identification of individuals within large wildlife populations is crucial for biological studies, ecological research, and wildlife conservation. Classic computer visi…