35 citations · 80 across the 8 of their papers we have counts for
9 papers
Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling
Xiaoyu Shi, Zhaoyang Huang, Fu-Yun Wang +9
We introduce Motion-I2V, a novel framework for consistent and controllable image-to-video generation (I2V). In contrast to previous methods that directly learn the complicated imag…
A Unified Conditional Framework for Diffusion-based Image Restoration
Yi Zhang, Xiaoyu Shi, Dasong Li +3
Diffusion Probabilistic Models (DPMs) have recently shown remarkable performance in image generation tasks, which are capable of generating highly realistic images. When adopting D…
KBNet: Kernel Basis Network for Image Restoration
Yi Zhang, Dasong Li, Xiaoyu Shi +5
How to aggregate spatial information plays an essential role in learning-based image restoration. Most existing CNN-based networks adopt static convolutional kernels to encode spat…
Learning Degradation Representations for Image Deblurring
Dasong Li, Yi Zhang, Ka Chun Cheung +3
In various learning-based image restoration tasks, such as image denoising and image super-resolution, the degradation representations were widely used to model the degradation pro…
A Simple Baseline for Video Restoration with Grouped Spatial-temporal Shift
Dasong Li, Xiaoyu Shi, Yi Zhang +5
Video restoration, which aims to restore clear frames from degraded videos, has numerous important applications. The key to video restoration depends on utilizing inter-frame infor…
Efficient Burst Raw Denoising with Variance Stabilization and Multi-frequency Denoising Network
Dasong Li, Yi Zhang, Ka Lung Law +3
With the growing popularity of smartphones, capturing high-quality images is of vital importance to smartphones. The cameras of smartphones have small apertures and small sensor ce…
IDR: Self-Supervised Image Denoising via Iterative Data Refinement
Yi Zhang, Dasong Li, Ka Lung Law +3
The lack of large-scale noisy-clean image pairs restricts supervised denoising methods' deployment in actual applications. While existing unsupervised methods are able to learn ima…
Rethinking Noise Synthesis and Modeling in Raw Denoising
Yi Zhang, Hongwei Qin, Xiaogang Wang +1
The lack of large-scale real raw image denoising dataset gives rise to challenges on synthesizing realistic raw image noise for training denoising models. However, the real raw ima…
On Reinforcement Learning for Full-length Game of StarCraft
Zhen-Jia Pang, Ruo-Ze Liu, Zhou-Yu Meng +3
StarCraft II poses a grand challenge for reinforcement learning. The main difficulties of it include huge state and action space and a long-time horizon. In this paper, we investig…