Research map / Detection and segmentation / Weakly supervised detection and segmentation
ComGAN: Unsupervised Disentanglement and Segmentation via Image Composition
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- GANSeg: Learning To Segment by Unsupervised Hierarchical Image Generation (CVPR 2022 · similarity 0.88)
- Object Segmentation Without Labels with Large-Scale Generative Models (ICML 2021 · similarity 0.87)
- FineGAN: Unsupervised Hierarchical Disentanglement for Fine-Grained Object Generation and Discovery (CVPR 2019 · similarity 0.87)
- Information-Theoretic Segmentation by Inpainting Error Maximization (CVPR 2021 · similarity 0.86)
- Finding an Unsupervised Image Segmenter in each of your Deep Generative Models (ICLR 2022 · similarity 0.86)
- Segment Anything without Supervision (NeurIPS 2024 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
