4 citations · 6 across the 10 of their papers we have counts for
16 papers · 1 filter
ProEdit: Inversion-based Editing From Prompts Done Right
Zhi Ouyang, Dian Zheng, Xiao-Ming Wu +4
Inversion-based visual editing provides an effective and training-free way to edit an image or a video based on user instructions. Existing methods typically inject source image in…
CoopDiff: Anticipating 3D Human-object Interactions via Contact-consistent Decoupled Diffusion
Xiaotong Lin, Tianming Liang, Jian-Fang Hu +5
3D human-object interaction (HOI) anticipation aims to predict the future motion of humans and their manipulated objects, conditioned on the historical context. Generally, the arti…
ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding
Yi-Xing Peng, Qize Yang, Yu-Ming Tang +4
Fine-grained understanding of human actions and poses in videos is essential for human-centric AI applications. In this work, we introduce ActionArt, a fine-grained video-caption d…
Modeling Multiple Normal Action Representations for Error Detection in Procedural Tasks
Wei-Jin Huang, Yuan-Ming Li, Zhi-Wei Xia +4
Error detection in procedural activities is essential for consistent and correct outcomes in AR-assisted and robotic systems. Existing methods often focus on temporal ordering erro…
Decoupled Distillation to Erase: A General Unlearning Method for Any Class-centric Tasks
Yu Zhou, Dian Zheng, Qijie Mo +3
In this work, we present DEcoupLEd Distillation To Erase (DELETE), a general and strong unlearning method for any class-centric tasks. To derive this, we first propose a theoretica…
ViSpeak: Visual Instruction Feedback in Streaming Videos
Shenghao Fu, Qize Yang, Yuan-Ming Li +6
Recent advances in Large Multi-modal Models (LMMs) are primarily focused on offline video understanding. Instead, streaming video understanding poses great challenges to recent mod…