52 citations · 82 across the 13 of their papers we have counts for
16 papers
Hyper-RED: Scalable Event Pre-training via Semantic Hypergraph Distillation
Meisen Wang, Zhiqiang Tian, Wei Bao +3
Event cameras have shown great potential for robust visual perception, yet scaling event representation learning remains challenging due to the scarcity of large-scale annotated ev…
GeoTrace: Geometry-Aware Trajectory Token Compression for Video Large Language Models
Guohuan Xie, Mengqi Lei, Chuan Shi +3
Although Video Large Language Models (Video LLMs) have shown strong performance in video understanding, their efficiency is still limited by the large number of visual tokens. Exis…
M^2C-EvDet: Multi-Domain Multi-Order Cross-Modal Knowledge Distillation for Event-based Object Detection
Wei Bao, Siqi Li, Shouan Pan +2
Event-based object Detection (EvDet), as a biologically inspired visual perception paradigm, demonstrates superior performance in scenarios demanding high temporal resolution and a…
Count Anything
Mengqi Lei, Shuokun Cheng, Wei Bao +4
Object counting remains fragmented across domain-specific datasets and task formulations, despite rapid progress in generalist vision models. Existing counting models are often tai…
Hypergraph as Language
Mengqi Lei, Guohuan Xie, Shihui Ying +6
Large language models (LLMs) have recently shown strong potential in modeling relational structures. However, existing approaches remain fundamentally graph-centric: they focus on…
Hyper-FSAD: Training-Free and Language-Free Few-Shot Anomaly Detection via Sparse Hyper Matching
Guohuan Xie, Xin He, Dingying Fan +2
Few-shot anomaly detection (FSAD) is particularly valuable when only a few normal images are available in a new target domain, while anomalous cases are rare, diverse, and difficul…
Rethinking Event-Based Object Detection through Representation-Level Temporal Aggregation and Model-Level Hypergraph Reasoning
Meisen Wang, Hao Deng, Wei Bao +5
Event cameras provide microsecond-level temporal resolution, low latency, and high dynamic range, offering potential for perception under fast motion and challenging illumination c…
RACANet: Reliability-Aware Crowd Anchor Network for RGB-T Crowd Counting
Jinghao Shi, Mengqi Lei, Kunliang He +3
RGB-Thermal (T) crowd counting aims to integrate visible-spectrum and thermal infrared information to improve the robustness of crowd density estimation in complex scenes. Although…
Hyper-FEOD: Sparse Hypergraph-Enhanced Frame-Event Object Detection with Fine-Grained MoE
Wei Bao, Yuehan Wang, Tianhang Zhou +1
The integration of frame-based RGB cameras with event streams constitutes a promising paradigm for robust object detection under challenging dynamic conditions. Nevertheless, effec…
I3DM: Implicit 3D-aware Memory Retrieval and Injection for Consistent Video Scene Generation
Jia Li, Han Yan, Yihang Chen +6
Despite remarkable progress in video generation, maintaining long-term scene consistency upon revisiting previously explored areas remains challenging. Existing solutions rely eith…
FineSkiing: A Fine-grained Benchmark for Skiing Action Quality Assessment
Yongji Zhang, Siqi Li, Yue Gao +1
Action Quality Assessment (AQA) aims to evaluate and score sports actions, which has attracted widespread interest in recent years. Existing AQA methods primarily predict scores ba…
H3Former: Hypergraph-based Semantic-Aware Aggregation via Hyperbolic Hierarchical Contrastive Loss for Fine-Grained Visual Classification
Yongji Zhang, Siqi Li, Kuiyang Huang +2
Fine-Grained Visual Classification (FGVC) remains a challenging task due to subtle inter-class differences and large intra-class variations. Existing approaches typically rely on f…
YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual Perception
Mengqi Lei, Siqi Li, Yihong Wu +7
The YOLO series models reign supreme in real-time object detection due to their superior accuracy and computational efficiency. However, both the convolutional architectures of YOL…
SoftHGNN: Soft Hypergraph Neural Networks for General Visual Recognition
Mengqi Lei, Yihong Wu, Siqi Li +4
Visual recognition relies on understanding the semantics of image tokens and their complex interactions. Mainstream self-attention methods, while effective at modeling global pair-…
ERetinex: Event Camera Meets Retinex Theory for Low-Light Image Enhancement
Xuejian Guo, Zhiqiang Tian, Yuehang Wang +4
Low-light image enhancement aims to restore the under-exposure image captured in dark scenarios. Under such scenarios, traditional frame-based cameras may fail to capture the struc…
Hypergraph-based Multi-View Action Recognition using Event Cameras
Yue Gao, Jiaxuan Lu, Siqi Li +2
Action recognition from video data forms a cornerstone with wide-ranging applications. Single-view action recognition faces limitations due to its reliance on a single viewpoint. I…