34 citations · 142 across the 36 of their papers we have counts for
18 papers
C-Procgen: Empowering Procgen with Controllable Contexts
Zhenxiong Tan, Kaixin Wang, Xinchao Wang
We present C-Procgen, an enhanced suite of environments on top of the Procgen benchmark. C-Procgen provides access to over 200 unique game contexts across 16 games. It allows for d…
Can SAM Boost Video Super-Resolution?
Zhihe Lu, Zeyu Xiao, Jiawang Bai +2
The primary challenge in video super-resolution (VSR) is to handle large motions in the input frames, which makes it difficult to accurately aggregate information from multiple fra…
Deep Graph Reprogramming
Yongcheng Jing, Chongbin Yuan, Li Ju +3
In this paper, we explore a novel model reusing task tailored for graph neural networks (GNNs), termed as "deep graph reprogramming". We strive to reprogram a pre-trained GNN, with…
Master: Meta Style Transformer for Controllable Zero-Shot and Few-Shot Artistic Style Transfer
Hao Tang, Songhua Liu, Tianwei Lin +4
Transformer-based models achieve favorable performance in artistic style transfer recently thanks to its global receptive field and powerful multi-head/layer attention operations.…
Segment Anything in Non-Euclidean Domains: Challenges and Opportunities
Yongcheng Jing, Xinchao Wang, Dacheng Tao
The recent work known as Segment Anything (SA) has made significant strides in pushing the boundaries of semantic segmentation into the era of foundation models. The impact of SA h…
Any-to-Any Style Transfer: Making Picasso and Da Vinci Collaborate
Songhua Liu, Jingwen Ye, Xinchao Wang
Style transfer aims to render the style of a given image for style reference to another given image for content reference, and has been widely adopted in artistic generation and im…