20 citations · 29 across the 12 of their papers we have counts for
10 papers · 1 filter
Spatially-guided Temporal Aggregation for Robust Event-RGB Optical Flow Estimation
Qianang Zhou, Junhui Hou, Meiyi Yang +3
Current optical flow methods exploit the stable appearance of frame (or RGB) data to establish robust correspondences across time. Event cameras, on the other hand, provide high-te…
ResFlow: Fine-tuning Residual Optical Flow for Event-based High Temporal Resolution Motion Estimation
Qianang Zhou, Zhiyu Zhu, Junhui Hou +3
Event cameras hold significant promise for high-temporal-resolution (HTR) motion estimation. However, estimating event-based HTR optical flow faces two key challenges: the absence…
Prune and Repaint: Content-Aware Image Retargeting for any Ratio
Feihong Shen, Chao Li, Yifeng Geng +2
Image retargeting is the task of adjusting the aspect ratio of images to suit different display devices or presentation environments. However, existing retargeting methods often st…
EventAug: Multifaceted Spatio-Temporal Data Augmentation Methods for Event-based Learning
Yukun Tian, Hao Chen, Yongjian Deng +4
The event camera has demonstrated significant success across a wide range of areas due to its low time latency and high dynamic range. However, the community faces challenges such…
Event-based Video Frame Interpolation with Edge Guided Motion Refinement
Yuhan Liu, Yongjian Deng, Hao Chen +3
Video frame interpolation, the process of synthesizing intermediate frames between sequential video frames, has made remarkable progress with the use of event cameras. These sensor…
Data-efficient Event Camera Pre-training via Disentangled Masked Modeling
Zhenpeng Huang, Chao Li, Hao Chen +3
In this paper, we present a new data-efficient voxel-based self-supervised learning method for event cameras. Our pre-training overcomes the limitations of previous methods, which…
Dissecting RGB-D Learning for Improved Multi-modal Fusion
Hao Chen, Haoran Zhou, Yunshu Zhang +2
In the RGB-D vision community, extensive research has been focused on designing multi-modal learning strategies and fusion structures. However, the complementary and fusion mechani…
Event Voxel Set Transformer for Spatiotemporal Representation Learning on Event Streams
Bochen Xie, Yongjian Deng, Zhanpeng Shao +2
Event cameras are neuromorphic vision sensors that record a scene as sparse and asynchronous event streams. Most event-based methods project events into dense frames and process th…
A Dynamic Graph CNN with Cross-Representation Distillation for Event-Based Recognition
Yongjian Deng, Hao Chen, Bochen Xie +2
Recent advances in event-based research prioritize sparsity and temporal precision. Approaches using dense frame-based representations processed via well-pretrained CNNs are being…
A Voxel Graph CNN for Object Classification with Event Cameras
Yongjian Deng, Hao Chen, Hai Liu +1
Event cameras attract researchers' attention due to their low power consumption, high dynamic range, and extremely high temporal resolution. Learning models on event-based object c…