69 citations · 158 across the 12 of their papers we have counts for
12 papers
Scaling Laws for Deepfake Detection
Wenhao Wang, Longqi Cai, Jusheng Zhang +3
This paper presents a systematic study of scaling laws for the deepfake detection task. Specifically, we analyze the model performance against the number of real image domains, dee…
Exploiting Category Names for Few-Shot Classification with Vision-Language Models
Taihong Xiao, Zirui Wang, Liangliang Cao +3
Vision-language foundation models pretrained on large-scale data provide a powerful tool for many visual understanding tasks. Notably, many vision-language models build two encoder…
FlowNAS: Neural Architecture Search for Optical Flow Estimation
Zhiwei Lin, Tingting Liang, Taihong Xiao +3
Existing optical flow estimators usually employ the network architectures typically designed for image classification as the encoder to extract per-pixel features. However, due to…
Adaptive Transformers for Robust Few-shot Cross-domain Face Anti-spoofing
Hsin-Ping Huang, Deqing Sun, Yaojie Liu +5
While recent face anti-spoofing methods perform well under the intra-domain setups, an effective approach needs to account for much larger appearance variations of images acquired…
Learning Contrastive Representation for Semantic Correspondence
Taihong Xiao, Sifei Liu, Shalini De Mello +3
Dense correspondence across semantically related images has been extensively studied, but still faces two challenges: 1) large variations in appearance, scale and pose exist even f…
Learnable Cost Volume Using the Cayley Representation
Taihong Xiao, Jinwei Yuan, Deqing Sun +4
Cost volume is an essential component of recent deep models for optical flow estimation and is usually constructed by calculating the inner product between two feature vectors. How…
Semi-Supervised Learning with Meta-Gradient
Xin-Yu Zhang, Taihong Xiao, Haolin Jia +2
In this work, we propose a simple yet effective meta-learning algorithm in semi-supervised learning. We notice that most existing consistency-based approaches suffer from overfitti…
Structured Sparsification with Joint Optimization of Group Convolution and Channel Shuffle
Xin-Yu Zhang, Kai Zhao, Taihong Xiao +2
Recent advances in convolutional neural networks(CNNs) usually come with the expense of excessive computational overhead and memory footprint. Network compression aims to alleviate…
Adversarial Learning of Privacy-Preserving and Task-Oriented Representations
Taihong Xiao, Yi-Hsuan Tsai, Kihyuk Sohn +2
Data privacy has emerged as an important issue as data-driven deep learning has been an essential component of modern machine learning systems. For instance, there could be a poten…
ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes
Taihong Xiao, Jiapeng Hong, Jinwen Ma
Recent studies on face attribute transfer have achieved great success. A lot of models are able to transfer face attributes with an input image. However, they suffer from three lim…
DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images
Taihong Xiao, Jiapeng Hong, Jinwen Ma
Disentangling factors of variation has become a very challenging problem on representation learning. Existing algorithms suffer from many limitations, such as unpredictable disenta…
GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data
Shuchang Zhou, Taihong Xiao, Yi Yang +3
Object Transfiguration replaces an object in an image with another object from a second image. For example it can perform tasks like "putting exactly those eyeglasses from image A…