https://github.com/likyoo/SegEarth-OV
공식 코드SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images
Papers with Code 아카이브
Open Vocabulary Semantic Segmentation
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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/linsun449/cliper.code
공식 코드https://github.com/lygsbw/umg-clip
공식 코드UMG-CLIP: A Unified Multi-Granularity Vision Generalist for Open-World Understanding
https://github.com/m-arda-aydn/itaclip
공식 코드https://github.com/mc-lan/proxyclip
공식 코드ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation
https://github.com/mendelxu/san
공식 코드Side Adapter Network for Open-Vocabulary Semantic Segmentation
https://github.com/mendelxu/zsseg.baseline
공식 코드A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Model
https://github.com/mlpc-ucsd/maskclip
공식 코드https://github.com/mustafa1728/wlsegnet
공식 코드A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation
https://github.com/nessessence/ZeroGuidanceSeg
공식 코드https://github.com/nvlabs/odise
공식 코드Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models
https://github.com/openrobotlab/ov_parts
공식 코드https://github.com/ozzyou/autoseg
공식 코드https://github.com/ram95d/ovose
공식 코드OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras
https://github.com/rezaqorbani/semla
공식 코드Semantic Library Adaptation: LoRA Retrieval and Fusion for Open-Vocabulary Semantic Segmentation
https://github.com/shjo-april/TTD
공식 코드TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias
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/workforai/scan
공식 코드Open-Vocabulary Segmentation with Semantic-Assisted Calibration
https://github.com/wusize/clipself
공식 코드CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction
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/yongliu20/SCAN
공식 코드Open-Vocabulary Segmentation with Semantic-Assisted Calibration
https://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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.