18 citations · 32 across the 16 of their papers we have counts for
6 papers · 1 filter
Deep Learning for Video Anomaly Detection: A Review
Peng Wu, Chengyu Pan, Yuting Yan +3
Video anomaly detection (VAD) aims to discover behaviors or events deviating from the normality in videos. As a long-standing task in the field of computer vision, VAD has witnesse…
Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts
Peng Wu, Xuerong Zhou, Guansong Pang +4
Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-level anomalous event detection with only coarse video-level annotations available. Existing wo…
Bracketing Image Restoration and Enhancement with High-Low Frequency Decomposition
Genggeng Chen, Kexin Dai, Kangzhen Yang +7
In real-world scenarios, due to a series of image degradations, obtaining high-quality, clear content photos is challenging. While significant progress has been made in synthesizin…
NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results
Xiaoning Liu, Zongwei Wu, Ao Li +109
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective netw…
CRNet: A Detail-Preserving Network for Unified Image Restoration and Enhancement Task
Kangzhen Yang, Tao Hu, Kexin Dai +6
In real-world scenarios, images captured often suffer from blurring, noise, and other forms of image degradation, and due to sensor limitations, people usually can only obtain low…
You Only Need One Color Space: An Efficient Network for Low-light Image Enhancement
Qingsen Yan, Yixu Feng, Cheng Zhang +5
Low-Light Image Enhancement (LLIE) task tends to restore the details and visual information from corrupted low-light images. Most existing methods learn the mapping function betwee…