6 citations · 6 across the 7 of their papers we have counts for
8 papers
Geometry-Instructed Video Editing
Chirui Chang, Xiaoyang Lyu, Yi-Hua Huang +7
Object-level geometric edits, including translating, rotating, scaling, duplicating, or removing an object, are routine operations in digital content creation (DCC) workflows, yet…
ASSIST-3D: Adapted Scene Synthesis for Class-Agnostic 3D Instance Segmentation
Shengchao Zhou, Jiehong Lin, Jiahui Liu +3
Class-agnostic 3D instance segmentation tackles the challenging task of segmenting all object instances, including previously unseen ones, without semantic class reliance. Current…
Equipping Vision Foundation Model with Mixture of Experts for Out-of-Distribution Detection
Shizhen Zhao, Jiahui Liu, Xin Wen +2
Pre-trained vision foundation models have transformed many computer vision tasks. Despite their strong ability to learn discriminative and generalizable features crucial for out-of…
Aligning Effective Tokens with Video Anomaly in Large Language Models
Yingxian Chen, Jiahui Liu, Ruidi Fan +6
Understanding abnormal events in videos is a vital and challenging task that has garnered significant attention in a wide range of applications. Although current video understandin…
Data Pruning by Information Maximization
Haoru Tan, Sitong Wu, Wei Huang +2
In this paper, we present InfoMax, a novel data pruning method, also known as coreset selection, designed to maximize the information content of selected samples while minimizing r…
Learning from Neighbors: Category Extrapolation for Long-Tail Learning
Shizhen Zhao, Xin Wen, Jiahui Liu +3
Balancing training on long-tail data distributions remains a long-standing challenge in deep learning. While methods such as re-weighting and re-sampling help alleviate the imbalan…
Can OOD Object Detectors Learn from Foundation Models?
Jiahui Liu, Xin Wen, Shizhen Zhao +2
Out-of-distribution (OOD) object detection is a challenging task due to the absence of open-set OOD data. Inspired by recent advancements in text-to-image generative models, such a…
Prototypical VoteNet for Few-Shot 3D Point Cloud Object Detection
Shizhen Zhao, Xiaojuan Qi
Most existing 3D point cloud object detection approaches heavily rely on large amounts of labeled training data. However, the labeling process is costly and time-consuming. This pa…