266 citations · 364 across the 9 of their papers we have counts for
9 papers
ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting
Zongsheng Yue, Jianyi Wang, Chen Change Loy
Diffusion-based image super-resolution (SR) methods are mainly limited by the low inference speed due to the requirements of hundreds or even thousands of sampling steps. Existing…
Exploiting Diffusion Prior for Real-World Image Super-Resolution
Jianyi Wang, Zongsheng Yue, Shangchen Zhou +2
We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution (SR). Specifically, by employing our t…
Exploring CLIP for Assessing the Look and Feel of Images
Jianyi Wang, Kelvin C. K. Chan, Chen Change Loy
Measuring the perception of visual content is a long-standing problem in computer vision. Many mathematical models have been developed to evaluate the look or quality of an image.…
SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
Ailing Zeng, Lei Yang, Xuan Ju +3
When analyzing human motion videos, the output jitters from existing pose estimators are highly-unbalanced with varied estimation errors across frames. Most frames in a video are r…
Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Video
Jianyi Wang, Xin Deng, Mai Xu +2
The past few years have witnessed fast development in video quality enhancement via deep learning. Existing methods mainly focus on enhancing the objective quality of compressed vi…
Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence
Yuhang Song, Andrzej Wojcicki, Thomas Lukasiewicz +6
Learning agents that are not only capable of taking tests, but also innovating is becoming a hot topic in AI. One of the most promising paths towards this vision is multi-agent lea…
Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz +4
Intrinsic rewards were introduced to simulate how human intelligence works; they are usually evaluated by intrinsically-motivated play, i.e., playing games without extrinsic reward…
Diversity-Driven Extensible Hierarchical Reinforcement Learning
Yuhang Song, Jianyi Wang, Thomas Lukasiewicz +2
Hierarchical reinforcement learning (HRL) has recently shown promising advances on speeding up learning, improving the exploration, and discovering intertask transferable skills. M…
Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach
Yuhang Song, Mai Xu, Jianyi Wang +3
Panoramic video provides immersive and interactive experience by enabling humans to control the field of view (FoV) through head movement (HM). Thus, HM plays a key role in modelin…