Papers with Code 아카이브

Unsupervised Semantic Segmentation

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하위 태스크: 1
평가표: 18
보존된 평가 기록: 97

Models that learn to segment each image (i.e. assign a class to every pixel) without seeing the ground truth labels.

<span style="color:grey; opacity: 0.6">( Image credit: SegSort: Segmentation by Discriminative Sorting of Segments )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ByungKwanLee/Causal-Unsupervised-Segmentation

공식 코드

Causal Unsupervised Semantic Segmentation

https://github.com/CVMI-Lab/SlotCon

공식 코드

Self-Supervised Visual Representation Learning with Semantic Grouping

https://github.com/ExplainableML/cosmos

공식 코드

COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training

https://github.com/LUSSeg/ImageNet-S

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Large-scale Unsupervised Semantic Segmentation

https://github.com/MCG-NKU/SERE

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SERE: Exploring Feature Self-relation for Self-supervised Transformer

https://github.com/MICV-yonsei/EAGLE

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EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation

https://github.com/NVlabs/GroupViT

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GroupViT: Semantic Segmentation Emerges from Text Supervision

https://github.com/NoelShin/reco

공식 코드

ReCo: Retrieve and Co-segment for Zero-shot Transfer

https://github.com/Qinying-Liu/TagAlign

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TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification

https://github.com/RyannDaGreat/peekaboo

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Peekaboo: Text to Image Diffusion Models are Zero-Shot Segmentors

https://github.com/ShenZheng2000/Semantic-Guided-Low-Light-Image-Enhancement

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Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancement

https://github.com/SonalKumar95/DatUS

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DatUS^2: Data-driven Unsupervised Semantic Segmentation with Pre-trained Self-supervised Vision Transformer

https://github.com/YuHengsss/Trident

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Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation

https://github.com/antoinehabis/Deep-ContourFlow

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Deep ContourFlow: Advancing Active Contours with Deep Learning

https://github.com/avaxiao/TextRegion

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TextRegion: Text-Aligned Region Tokens from Frozen Image-Text Models

https://github.com/bharathprabakaran/boundarycam

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ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images

https://github.com/bharathprabakaran/refit

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ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation using Object Border Fitting for Medical Images

https://github.com/castorini/daam

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What the DAAM: Interpreting Stable Diffusion Using Cross Attention

https://github.com/chdyshli/unsupervised-road-parsing

공식 코드

Applying Unsupervised Semantic Segmentation to High-Resolution UAV Imagery for Enhanced Road Scene Parsing

https://github.com/chongzhou96/maskclip

공식 코드

Extract Free Dense Labels from CLIP

https://github.com/damo-cv/transfgu

공식 코드

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

https://github.com/dogehhh/reclip

공식 코드

ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation

https://github.com/erikostrowski/perimeter-based-semantic-segmentation

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SILOP: An Automated Framework for Semantic Segmentation Using Image Labels Based on Object Perimeters

https://github.com/erikostrowski/silop

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SILOP: An Automated Framework for Semantic Segmentation Using Image Labels Based on Object Perimeters

https://github.com/facebookresearch/deepcluster

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Deep Clustering for Unsupervised Learning of Visual Features

https://github.com/hynnsk/PPAP

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Progressive Proxy Anchor Propagation for Unsupervised Semantic Segmentation

https://github.com/hynnsk/hp

공식 코드

Leveraging Hidden Positives for Unsupervised Semantic Segmentation

https://github.com/janghyuncho/PiCIE

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PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering

https://github.com/kaiizhang/mfa

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Multiple Fusion Adaptation: A Strong Framework for Unsupervised Semantic Segmentation Adaptation

https://github.com/kaiyizhang/AXform

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Attention-based Transformation from Latent Features to Point Clouds

https://github.com/kakaobrain/tcl

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Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs

https://github.com/leungtsang/cpcdr

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Copy-Pasting Coherent Depth Regions Improves Contrastive Learning for Urban-Scene Segmentation

https://github.com/linsun449/iseg.code

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iSeg: An Iterative Refinement-based Framework for Training-free Segmentation

https://github.com/linyq2117/tagclip

공식 코드

TagCLIP: A Local-to-Global Framework to Enhance Open-Vocabulary Multi-Label Classification of CLIP Without Training

https://github.com/liutongkun/comad

공식 코드

Component-aware anomaly detection framework for adjustable and logical industrial visual inspection

https://github.com/lukemelas/deep-spectral-segmentation

공식 코드

Deep Spectral Methods: A Surprisingly Strong Baseline for Unsupervised Semantic Segmentation and Localization

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