67 citations · 138 across the 14 of their papers we have counts for
14 papers
Generative Domain Adaptation for Face Anti-Spoofing
Qianyu Zhou, Ke-Yue Zhang, Taiping Yao +4
Face anti-spoofing (FAS) approaches based on unsupervised domain adaption (UDA) have drawn growing attention due to promising performances for target scenarios. Most existing UDA F…
Efficient Decoder-free Object Detection with Transformers
Peixian Chen, Mengdan Zhang, Yunhang Shen +5
Vision transformers (ViTs) are changing the landscape of object detection approaches. A natural usage of ViTs in detection is to replace the CNN-based backbone with a transformer-b…
Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization
Peixian Chen, Kekai Sheng, Mengdan Zhang +5
Open-vocabulary object detection (OVD) aims to scale up vocabulary size to detect objects of novel categories beyond the training vocabulary. Recent work resorts to the rich knowle…
Training-free Transformer Architecture Search
Qinqin Zhou, Kekai Sheng, Xiawu Zheng +5
Recently, Vision Transformer (ViT) has achieved remarkable success in several computer vision tasks. The progresses are highly relevant to the architecture design, then it is worth…
ARM: Any-Time Super-Resolution Method
Bohong Chen, Mingbao Lin, Kekai Sheng +5
This paper proposes an Any-time super-Resolution Method (ARM) to tackle the over-parameterized single image super-resolution (SISR) models. Our ARM is motivated by three observatio…
Reciprocal Normalization for Domain Adaptation
Zhiyong Huang, Kekai Sheng, Ke Li +5
Batch normalization (BN) is widely used in modern deep neural networks, which has been shown to represent the domain-related knowledge, and thus is ineffective for cross-domain tas…
Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer
Yifan Xu, Zhijie Zhang, Mengdan Zhang +6
Vision transformers (ViTs) have recently received explosive popularity, but the huge computational cost is still a severe issue. Since the computation complexity of ViT is quadrati…
Dual Reweighting Domain Generalization for Face Presentation Attack Detection
Shubao Liu, Ke-Yue Zhang, Taiping Yao +6
Face anti-spoofing approaches based on domain generalization (DG) have drawn growing attention due to their robustness for unseen scenarios. Previous methods treat each sample from…
Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing
Zhihong Chen, Taiping Yao, Kekai Sheng +5
Face anti-spoofing approach based on domain generalization(DG) has drawn growing attention due to its robustness forunseen scenarios. Existing DG methods assume that the do-main la…
Towards Corruption-Agnostic Robust Domain Adaptation
Yifan Xu, Kekai Sheng, Weiming Dong +3
Big progress has been achieved in domain adaptation in decades. Existing works are always based on an ideal assumption that testing target domain are i.i.d. with training target do…
On Evolving Attention Towards Domain Adaptation
Kekai Sheng, Ke Li, Xiawu Zheng +5
Towards better unsupervised domain adaptation (UDA). Recently, researchers propose various domain-conditioned attention modules and make promising progresses. However, considering…
Effective Label Propagation for Discriminative Semi-Supervised Domain Adaptation
Zhiyong Huang, Kekai Sheng, Weiming Dong +5
Semi-supervised domain adaptation (SSDA) methods have demonstrated great potential in large-scale image classification tasks when massive labeled data are available in the source d…
Dynamic Refinement Network for Oriented and Densely Packed Object Detection
Xingjia Pan, Yuqiang Ren, Kekai Sheng +5
Object detection has achieved remarkable progress in the past decade. However, the detection of oriented and densely packed objects remains challenging because of following inheren…
Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning
Kekai Sheng, Weiming Dong, Menglei Chai +6
Visual aesthetic assessment has been an active research field for decades. Although latest methods have achieved promising performance on benchmark datasets, they typically rely on…