69 citations · 148 across the 50 of their papers we have counts for
50 papers
Revisit the Imbalance Optimization in Multi-task Learning: An Experimental Analysis
Yihang Guo, Tianyuan Yu, Liang Bai +4
Multi-task learning (MTL) aims to build general-purpose vision systems by training a single network to perform multiple tasks jointly. While promising, its potential is often hinde…
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…
Chain of Methodologies: Scaling Test Time Computation without Training
Cong Liu, Jie Wu, Weigang Wu +3
Large Language Models (LLMs) often struggle with complex reasoning tasks due to insufficient in-depth insights in their training data, which are typically absent in publicly availa…
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…