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Open Vocabulary Semantic Segmentation

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하위 태스크: 1
평가표: 14
보존된 평가 기록: 124

Open-vocabulary semantic segmentation models aim to accurately assign a semantic label to each pixel in an image from a set of arbitrary open-vocabulary texts.

코드

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

https://github.com/FocoosAI/ShowOrTell

공식 코드

Show or Tell? A Benchmark To Evaluate Visual and Textual Prompts in Semantic Segmentation

https://github.com/Jazzcharles/OVSegmentor

공식 코드

Learning Open-vocabulary Semantic Segmentation Models From Natural Language Supervision

https://github.com/KU-CVLAB/CAT-Seg

공식 코드

CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation

https://github.com/LiBingyu01/FGA-seg

공식 코드

FGAseg: Fine-Grained Pixel-Text Alignment for Open-Vocabulary Semantic Segmentation

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

공식 코드

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

https://github.com/VCG-team/DiffSegmenter

공식 코드

Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter

https://github.com/Vibashan/PosSAM

공식 코드

PosSAM: Panoptic Open-vocabulary Segment Anything

https://github.com/amazon-science/prompt-pretraining

공식 코드

Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition

https://github.com/anonymouse-9c53tp182bvz/vireo

공식 코드

Leveraging Depth and Language for Open-Vocabulary Domain-Generalized Semantic Segmentation

https://github.com/arrowluo/segclip

공식 코드

SegCLIP: Patch Aggregation with Learnable Centers for Open-Vocabulary Semantic Segmentation

https://github.com/bytedance/fc-clip

공식 코드

Convolutions Die Hard: Open-Vocabulary Segmentation with Single Frozen Convolutional CLIP

https://github.com/chaofanma/Fantastic-Beasts-Datasets

공식 코드

AttrSeg: Open-Vocabulary Semantic Segmentation via Attribute Decomposition-Aggregation

https://github.com/chaofanma/fusioner

공식 코드

Open-vocabulary Semantic Segmentation with Frozen Vision-Language Models

https://github.com/conghan0808/deop

공식 코드

Open-Vocabulary Semantic Segmentation with Decoupled One-Pass Network

https://github.com/congvvc/HyperSeg

공식 코드

HyperSeg: Towards Universal Visual Segmentation with Large Language Model

https://github.com/dahyun-kang/lazygrounding

공식 코드

In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation

https://github.com/dingjiansw101/zegformer

공식 코드

Decoupling Zero-Shot Semantic Segmentation

https://github.com/dk-liang/uniseg3d

공식 코드

A Unified Framework for 3D Scene Understanding

https://github.com/dosowiechi/mlmp

공식 코드

Test-Time Adaptation of Vision-Language Models for Open-Vocabulary Semantic Segmentation

https://github.com/dvlab-research/Seg-Zero

공식 코드

Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement

https://github.com/dvlab-research/tagclip

공식 코드

TagCLIP: Improving Discrimination Ability of Open-Vocabulary Semantic Segmentation

https://github.com/ethz-asl/autolabel

공식 코드

Panoptic Vision-Language Feature Fields

https://github.com/ethz-asl/pvlff

공식 코드

Panoptic Vision-Language Feature Fields

https://github.com/facebookresearch/ov-seg

공식 코드

Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP

https://github.com/hanzy1996/openseg-r

공식 코드

OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning

https://github.com/hustvl/maskadapter

공식 코드

Mask-Adapter: The Devil is in the Masks for Open-Vocabulary Segmentation

https://github.com/hvision-nku/maskclippp

공식 코드

MaskCLIP++: A Mask-Based CLIP Fine-tuning Framework for Open-Vocabulary Image Segmentation

https://github.com/jiaosiyu1999/MAFT-Plus

공식 코드

Collaborative Vision-Text Representation Optimizing for Open-Vocabulary Segmentation

https://github.com/jiaosiyu1999/maft

공식 코드

Learning Mask-aware CLIP Representations for Zero-Shot Segmentation

https://github.com/jun-cen/segmentanyrgbd

공식 코드

SAD: Segment Any RGBD

https://github.com/kaist-cvml-lab/part-clipseg

공식 코드

Understanding Multi-Granularity for Open-Vocabulary Part Segmentation

https://github.com/kaist-cvml/part-catseg

공식 코드

Fine-Grained Image-Text Correspondence with Cost Aggregation for Open-Vocabulary Part Segmentation

https://github.com/kaist-cvml/part-clipseg

공식 코드

Understanding Multi-Granularity for Open-Vocabulary Part Segmentation

https://github.com/kakaobrain/tcl

공식 코드

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

https://github.com/leaves162/cliptrase

공식 코드

Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation

https://github.com/letitiabanana/pnp-ovss

공식 코드

Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models

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