84 citations · 85 across the 2 of their papers we have counts for
8 papers · 1 filter
One Step Diffusion-based Super-Resolution with Time-Aware Distillation
Xiao He, Huaao Tang, Zhijun Tu +8
Diffusion-based image super-resolution (SR) methods have shown promise in reconstructing high-resolution images with fine details from low-resolution counterparts. However, these a…
LIPT: Latency-aware Image Processing Transformer
Junbo Qiao, Wei Li, Haizhen Xie +5
Transformer is leading a trend in the field of image processing. Despite the great success that existing lightweight image processing transformers have achieved, they are tailored…
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li +5
Knowledge distillation (KD) is a promising yet challenging model compression technique that transfers rich learning representations from a well-performing but cumbersome teacher mo…
Distilling Semantic Priors from SAM to Efficient Image Restoration Models
Quan Zhang, Xiaoyu Liu, Wei Li +6
In image restoration (IR), leveraging semantic priors from segmentation models has been a common approach to improve performance. The recent segment anything model (SAM) has emerge…
IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions
Zhijun Tu, Kunpeng Du, Hanting Chen +4
Recent advances have demonstrated the powerful capability of transformer architecture in image restoration. However, our analysis indicates that existing transformerbased methods c…
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Jianyuan Guo, Hanting Chen, Chengcheng Wang +3
Recent advancements in large language models have sparked interest in their extraordinary and near-superhuman capabilities, leading researchers to explore methods for evaluating an…