most citedTowards Small Object Editing: A Benchmark Dataset and A Training-Free Approach

288 citations · 294 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024★ 288 cited

Towards Small Object Editing: A Benchmark Dataset and A Training-Free Approach

Qihe Pan, Zhen Zhao, Zicheng Wang +5

A plethora of text-guided image editing methods has recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models especially St…

cs.CV2024

SOEDiff: Efficient Distillation for Small Object Editing

Yiming Wu, Qihe Pan, Zhen Zhao +3

In this paper, we delve into a new task known as small object editing (SOE), which focuses on text-based image inpainting within a constrained, small-sized area. Despite the remark…

cs.CV2024

Training-Free Unsupervised Prompt for Vision-Language Models

Sifan Long, Linbin Wang, Zhen Zhao +4

Prompt learning has become the most effective paradigm for adapting large pre-trained vision-language models (VLMs) to downstream tasks. Recently, unsupervised prompt tuning method…

eess.IV2024★ 1 cited

Troublemaker Learning for Low-Light Image Enhancement

Yinghao Song, Zhiyuan Cao, Wanhong Xiang +5

Low-light image enhancement (LLIE) restores the color and brightness of underexposed images. Supervised methods suffer from high costs in collecting low/normal-light image pairs. U…

cs.CV2023★ 5 cited

HAP: Structure-Aware Masked Image Modeling for Human-Centric Perception

Junkun Yuan, Xinyu Zhang, Hao Zhou +12

Model pre-training is essential in human-centric perception. In this paper, we first introduce masked image modeling (MIM) as a pre-training approach for this task. Upon revisiting…