Papers with Code 아카이브

2D Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

17

평가표

11

보존된 평가 기록

42

코드

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

https://github.com/leongdong/bias-decomposition-networks

공식 코드

Unsupervised Decomposition Networks for Bias Field Correction in MR Image

https://github.com/leonlha/kinematics-afr

공식 코드

Efficient Frame Extraction: A Novel Approach Through Frame Similarity and Surgical Tool Tracking for Video Segmentation

https://github.com/leonnnop/locater

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Local-Global Context Aware Transformer for Language-Guided Video Segmentation

https://github.com/levayz/dinov2-based-self-supervised-learning

공식 코드

DINOv2 based Self Supervised Learning For Few Shot Medical Image Segmentation

https://github.com/levayz/protosam

공식 코드

ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models

https://github.com/lhaof/asa

공식 코드

Attentive Symmetric Autoencoder for Brain MRI Segmentation

https://github.com/lhaof/nnmamba

공식 코드

nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model

https://github.com/lhaof/nudiff

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Diffusion-based Data Augmentation for Nuclei Image Segmentation

https://github.com/lhc1224/OSAD_Net

공식 코드

One-Shot Object Affordance Detection in the Wild

https://github.com/lhoangan/341n143

공식 코드

Three for one and one for three: Flow, Segmentation, and Surface Normals

https://github.com/lhoangan/multas

공식 코드

Box for Mask and Mask for Box: weak losses for multi-task partially supervised learning

https://github.com/lhoyer/hrda

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Domain Adaptive and Generalizable Network Architectures and Training Strategies for Semantic Image Segmentation

https://github.com/liamchalcroft/mdunet

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Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation

https://github.com/liamheng/non-iid_medical_image_segmentation

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Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation

https://github.com/liar-zzy/benchmarking-ultra-high-definition-single-image-reflection-removal

공식 코드

Benchmarking Ultra-High-Definition Image Reflection Removal

https://github.com/liat-s/radar_occupancy_grid

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Road Scene Understanding by Occupancy Grid Learning from Sparse Radar Clusters using Semantic Segmentation

https://github.com/liavassif/BU-TD

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Image interpretation by iterative bottom-up top-down processing

https://github.com/lich0031/AIDE

공식 코드

Annotation-efficient deep learning for automatic medical image segmentation

https://github.com/lids-unicamp/rethinking-interactive-image-segmentation

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Rethinking Interactive Image Segmentation: Feature Space Annotation

https://github.com/lijuncen/Sentiment-and-Style-Transfer

공식 코드

Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer

https://github.com/lijunzhang01/cefa

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A Plug-and-Play Method for Rare Human-Object Interactions Detection by Bridging Domain Gap

https://github.com/lik1996/icmformer

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Interactive Image Segmentation with Cross-Modality Vision Transformers

https://github.com/likojack/odam

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ODAM: Object Detection, Association, and Mapping using Posed RGB Video

https://github.com/lili0415/psg-biased-annotation

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Panoptic Scene Graph Generation with Semantics-Prototype Learning

https://github.com/liliu-avril/Awesome-Segment-Anything

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Segment Anything for Videos: A Systematic Survey

https://github.com/lilydaytoy/openpvsg

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Panoptic Video Scene Graph Generation

https://github.com/lilydaytoy/pvsgannotation

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Panoptic Video Scene Graph Generation

https://github.com/lilygoli/longitudinalCOVID

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Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs

https://github.com/lim-anggun/FgSegNet

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Foreground Segmentation Using a Triplet Convolutional Neural Network for Multiscale Feature Encoding

https://github.com/lim-anggun/FgSegNet_v2

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Learning Multi-scale Features for Foreground Segmentation

https://github.com/lime-j/RDNet

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Reversible Decoupling Network for Single Image Reflection Removal

https://github.com/limingxing00/rde-vos-cvpr2022

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Recurrent Dynamic Embedding for Video Object Segmentation

https://github.com/lin-tianyu/stable-diffusion-seg

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Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse Process

https://github.com/linchenq/transdeformer-mesh

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Attention-based Shape-Deformation Networks for Artifact-Free Geometry Reconstruction of Lumbar Spine from MR Images

https://github.com/linear95/rlm

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Replacing Language Model for Style Transfer

https://github.com/linfengyuan1997/losh

공식 코드

LoSh: Long-Short Text Joint Prediction Network for Referring Video Object Segmentation

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