4 citations · 7 across the 10 of their papers we have counts for
9 papers
Learning Expressive And Generalizable Motion Features For Face Forgery Detection
Jingyi Zhang, Peng Zhang, Jingjing Wang +2
Previous face forgery detection methods mainly focus on appearance features, which may be easily attacked by sophisticated manipulation. Considering the majority of current face ma…
CLIP-Gaze: Towards General Gaze Estimation via Visual-Linguistic Model
Pengwei Yin, Guanzhong Zeng, Jingjing Wang +1
Gaze estimation methods often experience significant performance degradation when evaluated across different domains, due to the domain gap between the testing and training data. E…
"Lossless" Compression of Deep Neural Networks: A High-dimensional Neural Tangent Kernel Approach
Lingyu Gu, Yongqi Du, Yuan Zhang +4
Modern deep neural networks (DNNs) are extremely powerful; however, this comes at the price of increased depth and having more parameters per layer, making their training and infer…
Adapt Anything: Tailor Any Image Classifiers across Domains And Categories Using Text-to-Image Diffusion Models
Weijie Chen, Haoyu Wang, Shicai Yang +6
We do not pursue a novel method in this paper, but aim to study if a modern text-to-image diffusion model can tailor any task-adaptive image classifier across domains and categorie…
1st Place Solution for ECCV 2022 OOD-CV Challenge Object Detection Track
Wei Zhao, Binbin Chen, Weijie Chen +4
OOD-CV challenge is an out-of-distribution generalization task. To solve this problem in object detection track, we propose a simple yet effective Generalize-then-Adapt (G&A) frame…
1st Place Solution for ECCV 2022 OOD-CV Challenge Image Classification Track
Yilu Guo, Xingyue Shi, Weijie Chen +4
OOD-CV challenge is an out-of-distribution generalization task. In this challenge, our core solution can be summarized as that Noisy Label Learning Is A Strong Test-Time Domain Ada…