Papers with Code 아카이브

2D Semantic Segmentation

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하위 태스크

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평가표

11

보존된 평가 기록

42

코드

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

https://github.com/starbucks-drinker/mi-segnet

공식 코드

MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization

https://github.com/starrah/dmh-net

공식 코드

3D Room Layout Estimation from a Cubemap of Panorama Image via Deep Manhattan Hough Transform

https://github.com/statmlben/rankseg

공식 코드

RankSEG: A Consistent Ranking-based Framework for Segmentation

https://github.com/staymylove/3DMIT

공식 코드

3DMIT: 3D Multi-modal Instruction Tuning for Scene Understanding

https://github.com/stefan-ainetter/SCANnotatepp

공식 코드

Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene Understanding

https://github.com/steff-farley/AFM-image-segmentation

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Improving the Segmentation of Scanning Probe Microscope Images using Convolutional Neural Networks

https://github.com/stefvk/elliptical-attention

공식 코드

Elliptical Attention

https://github.com/stegmuel/croc

공식 코드

CrOC: Cross-View Online Clustering for Dense Visual Representation Learning

https://github.com/stelzner/obsurf

공식 코드

Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation

https://github.com/steve-tod/stfc3

공식 코드

Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning

https://github.com/sthalham/tram3d

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Self-supervised Vision Transformers for 3D Pose Estimation of Novel Objects

https://github.com/stoa-xh91/humandensepose

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KTN: Knowledge Transfer Network for Learning Multi-person 2D-3D Correspondences

https://github.com/strivezs/alps

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ALPS: An Auto-Labeling and Pre-training Scheme for Remote Sensing Segmentation With Segment Anything Model

https://github.com/stuliu/dfc2025track1

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Learning from Noisy Pseudo-labels for All-Weather Land Cover Mapping

https://github.com/subtri/video_inference

공식 코드

Semantic Video Segmentation : Exploring Inference Efficiency

https://github.com/suhaisheng/robosense

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RoboSense: Large-scale Dataset and Benchmark for Egocentric Robot Perception and Navigation in Crowded and Unstructured Environments

https://github.com/suhas-srinath/genselfdiff-his

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GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentation

https://github.com/suhwan-cho/FindTrack

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Find First, Track Next: Decoupling Identification and Propagation in Referring Video Object Segmentation

https://github.com/suhwan-cho/bmvos

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Pixel-Level Bijective Matching for Video Object Segmentation

https://github.com/suhwan-cho/tbd

공식 코드

Tackling Background Distraction in Video Object Segmentation

https://github.com/suhwan-cho/tmo

공식 코드

Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation

https://github.com/sulaimanvesal/PointCloudUDA

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Adapt Everywhere: Unsupervised Adaptation of Point-Clouds and Entropy Minimisation for Multi-modal Cardiac Image Segmentation

https://github.com/suletekkesinoglu/xai_llm_rag

공식 코드

From Feature Importance to Natural Language Explanations Using LLMs with RAG

https://github.com/sun-1024/da-transunet

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DA-TransUNet: Integrating Spatial and Channel Dual Attention with Transformer U-Net for Medical Image Segmentation

https://github.com/sunalbert/Sequential-patch-based-segmentation

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Interactive Medical Image Segmentation via Point-Based Interaction and Sequential Patch Learning

https://github.com/sunfan-bvb/boundarydouloss

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Boundary Difference Over Union Loss For Medical Image Segmentation

https://github.com/sungyeonparkk/nuplanqa

공식 코드

NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language Models

https://github.com/sunjesse/shape-attentive-unet

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SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation

https://github.com/sunset1995/HoHoNet

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HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features

https://github.com/sunset1995/HorizonNet

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HorizonNet: Learning Room Layout with 1D Representation and Pano Stretch Data Augmentation

https://github.com/super-tadory/primgeoseg

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Primitive Geometry Segment Pre-training for 3D Medical Image Segmentation

https://github.com/supreethmv/NISQ-Seg

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Qubit-efficient Variational Quantum Algorithms for Image Segmentation

https://github.com/supreethmv/q-seg

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Q-Seg: Quantum Annealing-Based Unsupervised Image Segmentation

https://github.com/suprosanna/relationformer

공식 코드

Relationformer: A Unified Framework for Image-to-Graph Generation

https://github.com/suuujm/spss

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Self-Paced Sample Selection for Barely-Supervised Medical Image Segmentation

https://github.com/suwesh/parallel-perception-network

공식 코드

Parallel Neural Computing for Scene Understanding from LiDAR Perception in Autonomous Racing

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.