most citedAIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

16 citations · 41 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV20231 cited

StyleSync: High-Fidelity Generalized and Personalized Lip Sync in Style-based Generator

Jiazhi Guan, Zhanwang Zhang, Hang Zhou +8

Despite recent advances in syncing lip movements with any audio waves, current methods still struggle to balance generation quality and the model's generalization ability. Previous…

cs.CV20232 cited

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.…

cs.CV2023

LMR: A Large-Scale Multi-Reference Dataset for Reference-based Super-Resolution

Lin Zhang, Xin Li, Dongliang He +2

It is widely agreed that reference-based super-resolution (RefSR) achieves superior results by referring to similar high quality images, compared to single image super-resolution (…

eess.IV202216 cited

AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Xin Li +49

This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compress…

cs.CV2022

Boosting Video-Text Retrieval with Explicit High-Level Semantics

Haoran Wang, Di Xu, Dongliang He +4

Video-text retrieval (VTR) is an attractive yet challenging task for multi-modal understanding, which aims to search for relevant video (text) given a query (video). Existing metho…

cs.CV20221 cited

NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition

Boyang Xia, Wenhao Wu, Haoran Wang +5

It is challenging for artificial intelligence systems to achieve accurate video recognition under the scenario of low computation costs. Adaptive inference based efficient video re…