5 citations · 6 across the 5 of their papers we have counts for
6 papers · 1 filter
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)
Ya-nan Guan, Shaonan Zhang, Hang Guo +55
In this paper, we present a comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI Flash Portrait. Despite sign…
PersonificationNet: Making customized subject act like a person
Tianchu Guo, Pengyu Li, Biao Wang +1
Recently customized generation has significant potential, which uses as few as 3-5 user-provided images to train a model to synthesize new images of a specified subject. Though sub…
Learning Polysemantic Spoof Trace: A Multi-Modal Disentanglement Network for Face Anti-spoofing
Kaicheng Li, Hongyu Yang, Binghui Chen +3
Along with the widespread use of face recognition systems, their vulnerability has become highlighted. While existing face anti-spoofing methods can be generalized between attack t…
Dense Learning based Semi-Supervised Object Detection
Binghui Chen, Pengyu Li, Xiang Chen +3
Semi-supervised object detection (SSOD) aims to facilitate the training and deployment of object detectors with the help of a large amount of unlabeled data. Though various self-tr…
Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting
Binghui Chen, Zhaoyi Yan, Ke Li +4
In crowd counting, due to the problem of laborious labelling, it is perceived intractability of collecting a new large-scale dataset which has plentiful images with large diversity…
Continual Local Replacement for Few-shot Learning
Canyu Le, Zhonggui Chen, Xihan Wei +2
The goal of few-shot learning is to learn a model that can recognize novel classes based on one or few training data. It is challenging mainly due to two aspects: (1) it lacks good…