https://github.com/rezaqorbani/semla
공식 코드Semantic Library Adaptation: LoRA Retrieval and Fusion for Open-Vocabulary Semantic Segmentation
Papers with Code 아카이브
Open-Vocabulary Semantic Segmentation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sinahmr/naclip
공식 코드Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation
https://github.com/slonetime/ebseg
공식 코드Open-Vocabulary Semantic Segmentation with Image Embedding Balancing
https://github.com/valkyrja3607/maskdiffusion
공식 코드MaskDiffusion: Exploiting Pre-trained Diffusion Models for Semantic Segmentation
https://github.com/valkyrja3607/tag
공식 코드https://github.com/vladan-stojnic/lposs
공식 코드LPOSS: Label Propagation Over Patches and Pixels for Open-vocabulary Semantic Segmentation
https://github.com/wangys16/gov-nesf
공식 코드GOV-NeSF: Generalizable Open-Vocabulary Neural Semantic Fields
https://github.com/wangzy22/xmask3d
공식 코드XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation
https://github.com/wysoczanska/clip-diy
공식 코드CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free
https://github.com/wysoczanska/clip_dinoiser
공식 코드CLIP-DINOiser: Teaching CLIP a few DINO tricks for open-vocabulary semantic segmentation
https://github.com/xb534/sed
공식 코드SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation
https://github.com/xiweix/reme
공식 코드ReME: A Data-Centric Framework for Training-Free Open-Vocabulary Segmentation
https://github.com/xmed-lab/clip_surgery
공식 코드A Closer Look at the Explainability of Contrastive Language-Image Pre-training
https://github.com/yasserben/floss
공식 코드https://github.com/zdk258/CorrCLIP
공식 코드https://github.com/zlai0/s-seg
공식 코드https://github.com/blumenstiel/CAT-Seg-MESS
CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation
https://github.com/blumenstiel/SAN-MESS
Side Adapter Network for Open-Vocabulary Semantic Segmentation
https://github.com/earth-insights/samroadplus
SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images
https://github.com/facebookresearch/dinov2
DINOv2 Meets Text: A Unified Framework for Image- and Pixel-Level Vision-Language Alignment
https://github.com/ferenas/pgseg
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation
https://github.com/lchen1019/ERR-Seg
Efficient Redundancy Reduction for Open-Vocabulary Semantic Segmentation
https://github.com/paulcouairon/diffcut
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive Learning
https://github.com/xmed-lab/clipn
A Closer Look at the Explainability of Contrastive Language-Image Pre-training
https://github.com/xujxyang/opentrans
Global Knowledge Calibration for Fast Open-Vocabulary Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.