activity
20182026
most citedEDVR: Video Restoration with Enhanced Deformable Convolutional Networks

62 citations · 162 across the 16 of their papers we have counts for

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29 papers · 1 filter

cs.CV2026

DUO-VSR: Dual-Stream Distillation for One-Step Video Super-Resolution

Zhengyao Lv, Menghan Xia, Xintao Wang +1

Diffusion-based video super-resolution (VSR) has recently achieved remarkable fidelity but still suffers from prohibitive sampling costs. While distribution matching distillation (…

cs.CV20241 cited

Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

Fanghua Yu, Jinjin Gu, Zheyuan Li +6

We introduce SUPIR (Scaling-UP Image Restoration), a groundbreaking image restoration method that harnesses generative prior and the power of model scaling up. Leveraging multi-mod…

cs.CV2023

Unifying Image Processing as Visual Prompting Question Answering

Yihao Liu, Xiangyu Chen, Xianzheng Ma +4

Image processing is a fundamental task in computer vision, which aims at enhancing image quality and extracting essential features for subsequent vision applications. Traditionally…

cs.CV2023

HAT: Hybrid Attention Transformer for Image Restoration

Xiangyu Chen, Xintao Wang, Wenlong Zhang +4

Transformer-based methods have shown impressive performance in image restoration tasks, such as image super-resolution and denoising. However, we find that these networks can only…

cs.CV202310 cited

Planting a SEED of Vision in Large Language Model

Yuying Ge, Yixiao Ge, Ziyun Zeng +2

We present SEED, an elaborate image tokenizer that empowers Large Language Models (LLMs) with the emergent ability to SEE and Draw at the same time. Research on image tokenizers ha…

cs.CV20231 cited

GET3D--: Learning GET3D from Unconstrained Image Collections

Fanghua Yu, Xintao Wang, Zheyuan Li +3

The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generat…