activity
20172022
most citedLearning to Predict Layout-to-image Conditional Convolutions for Semantic Image Synthesis

92 citations · 328 across the 18 of their papers we have counts for

collaborators

29 papers

cs.CV20223 cited

PalGAN: Image Colorization with Palette Generative Adversarial Networks

Yi Wang, Menghan Xia, Lu Qi +2

Multimodal ambiguity and color bleeding remain challenging in colorization. To tackle these problems, we propose a new GAN-based colorization approach PalGAN, integrated with palet…

cs.CV2022

X-Learner: Learning Cross Sources and Tasks for Universal Visual Representation

Yinan He, Gengshi Huang, Siyu Chen +7

In computer vision, pre-training models based on largescale supervised learning have been proven effective over the past few years. However, existing works mostly focus on learning…

cs.CV20222 cited

Democratizing Contrastive Language-Image Pre-training: A CLIP Benchmark of Data, Model, and Supervision

Yufeng Cui, Lichen Zhao, Feng Liang +2

Contrastive Language-Image Pretraining (CLIP) has emerged as a novel paradigm to learn visual models from language supervision. While researchers continue to push the frontier of C…

cs.CV2022

RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-training

Luya Wang, Feng Liang, Yangguang Li +3

Recently, self-supervised vision transformers have attracted unprecedented attention for their impressive representation learning ability. However, the dominant method, contrastive…

cs.CV20217 cited

Few-Shot Domain Expansion for Face Anti-Spoofing

Bowen Yang, Jing Zhang, Zhenfei Yin +1

Face anti-spoofing (FAS) is an indispensable and widely used module in face recognition systems. Although high accuracy has been achieved, a FAS system will never be perfect due to…

cs.CV2021

ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis

Yinan He, Bei Gan, Siyu Chen +6

The rapid progress of photorealistic synthesis techniques has reached at a critical point where the boundary between real and manipulated images starts to blur. Thus, benchmarking…