SOTAVerified

Dichotomous Image Segmentation

Currently, existing image segmentation tasks mainly focus on segmenting objects with specific characteristics, e.g., salient, camouflaged, meticulous, or specific categories. Most of them have the same input/output formats, and barely use exclusive mechanisms designed for segmenting targets in their models, which means almost all tasks are dataset-dependent. Thus, it is very promising to formulate a category-agnostic DIS task for accurately segmenting objects with different structure complexities, regardless of their characteristics. Compared with semantic segmentation, the proposed DIS task usually focuses on images with single or a few targets, from which getting richer accurate details of each target is more feasible.

Papers

Showing 2128 of 28 papers

TitleStatusHype
Searching for MobileNetV3Code1
BiSeNet: Bilateral Segmentation Network for Real-time Semantic SegmentationCode1
Rethinking Atrous Convolution for Semantic Image SegmentationCode1
Pyramid Scene Parsing NetworkCode1
BEN: Using Confidence-Guided Matting for Dichotomous Image SegmentationCode0
Mask Factory: Towards High-quality Synthetic Data Generation for Dichotomous Image Segmentation0
Promoting Segment Anything Model towards Highly Accurate Dichotomous Image Segmentation0
ICNet for Real-Time Semantic Segmentation on High-Resolution ImagesCode0
Show:102550
← PrevPage 3 of 3Next →

No leaderboard results yet.