8 citations · 8 across the 6 of their papers we have counts for
8 papers
WAT: Online Video Understanding Needs Watching Before Thinking
Zifan Han, Hongbo Sun, Jinglin Xu +6
Multimodal Large Language Models (MLLMs) have shown strong capabilities in image understanding, motivating recent efforts to extend them to video reasoning. However, existing Video…
HunyuanOCR Technical Report
Hunyuan Vision Team, Pengyuan Lyu, Xingyu Wan +29
This paper presents HunyuanOCR, a commercial-grade, open-source, and lightweight (1B parameters) Vision-Language Model (VLM) dedicated to OCR tasks. The architecture comprises a Na…
Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection
Canhui Tang, Sanping Zhou, Haoyue Shi +1
Zero-Shot Video Anomaly Detection (ZS-VAD) requires temporally localizing anomalies without target domain training data, which is a crucial task due to various practical concerns,…
TSPO: Temporal Sampling Policy Optimization for Long-form Video Language Understanding
Canhui Tang, Zifan Han, Hongbo Sun +7
Multimodal Large Language Models (MLLMs) have demonstrated significant progress in vision-language tasks, yet they still face challenges when processing long-duration video inputs.…
PARE-Net: Position-Aware Rotation-Equivariant Networks for Robust Point Cloud Registration
Runzhao Yao, Shaoyi Du, Wenting Cui +2
Learning rotation-invariant distinctive features is a fundamental requirement for point cloud registration. Existing methods often use rotation-sensitive networks to extract featur…
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection
Canhui Tang, Sanping Zhou, Yizhe Li +2
With the wide application of knowledge distillation between an ImageNet pre-trained teacher model and a learnable student model, unsupervised anomaly detection has witnessed a sign…
HD2Reg: Hierarchical Descriptors and Detectors for Point Cloud Registration
Canhui Tang, Yiheng Li, Shaoyi Du +2
Feature Descriptors and Detectors are two main components of feature-based point cloud registration. However, little attention has been drawn to the explicit representation of loca…
HybridPoint: Point Cloud Registration Based on Hybrid Point Sampling and Matching
Yiheng Li, Canhui Tang, Runzhao Yao +3
Patch-to-point matching has become a robust way of point cloud registration. However, previous patch-matching methods employ superpoints with poor localization precision as nodes,…