most citedSegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

487 citations · 493 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

SLAN: Self-Locator Aided Network for Cross-Modal Understanding

Jiang-Tian Zhai, Qi Zhang, Tong Wu +4

Learning fine-grained interplay between vision and language allows to a more accurate understanding for VisionLanguage tasks. However, it remains challenging to extract key image r…

cs.CV2022

ClipCrop: Conditioned Cropping Driven by Vision-Language Model

Zhihang Zhong, Mingxi Cheng, Zhirong Wu +7

Image cropping has progressed tremendously under the data-driven paradigm. However, current approaches do not account for the intentions of the user, which is an issue especially w…

cs.CV20225 cited

Dual Pyramid Generative Adversarial Networks for Semantic Image Synthesis

Shijie Li, Ming-Ming Cheng, Juergen Gall

The goal of semantic image synthesis is to generate photo-realistic images from semantic label maps. It is highly relevant for tasks like content generation and image editing. Curr…

cs.CV2022487 cited

SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentation

Meng-Hao Guo, Cheng-Ze Lu, Qibin Hou +3

We present SegNeXt, a simple convolutional network architecture for semantic segmentation. Recent transformer-based models have dominated the field of semantic segmentation due to…

cs.CV20221 cited

Interactive Style Transfer: All is Your Palette

Zheng Lin, Zhao Zhang, Kang-Rui Zhang +2

Neural style transfer (NST) can create impressive artworks by transferring reference style to content image. Current image-to-image NST methods are short of fine-grained controls,…