70 citations · 76 across the 18 of their papers we have counts for
6 papers · 1 filter
Benchmarking and Enhancing VLM for Compressed Image Understanding
Zifu Zhang, Tongda Xu, Siqi Li +4
With the rapid development of Vision-Language Models (VLMs) and the growing demand for their applications, efficient compression of the image inputs has become increasingly importa…
Burst Image Quality Assessment: A New Benchmark and Unified Framework for Multiple Downstream Tasks
Xiaoye Liang, Lai Jiang, Minglang Qiao +6
In recent years, the development of burst imaging technology has improved the capture and processing capabilities of visual data, enabling a wide range of applications. However, th…
Breaking the Multi-Enhancement Bottleneck: Domain-Consistent Quality Enhancement for Compressed Images
Qunliang Xing, Mai Xu, Jing Yang +1
Quality enhancement methods have been widely integrated into visual communication pipelines to mitigate artifacts in compressed images. Ideally, these quality enhancement methods s…
Hierarchical Semantic Compression for Consistent Image Semantic Restoration
Shengxi Li, Zifu Zhang, Mai Xu +3
The emerging semantic compression has been receiving increasing research efforts most recently, capable of achieving high fidelity restoration during compression, even at extremely…
Continuous Patch Stitching for Block-wise Image Compression
Zifu Zhang, Shengxi Li, Henan Liu +2
Most recently, learned image compression methods have outpaced traditional hand-crafted standard codecs. However, their inference typically requires to input the whole image at the…
InstructOCR: Instruction Boosting Scene Text Spotting
Chen Duan, Qianyi Jiang, Pei Fu +5
In the field of scene text spotting, previous OCR methods primarily relied on image encoders and pre-trained text information, but they often overlooked the advantages of incorpora…