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/cjm-sfw/Uniparser

공식 코드

UniParser: Multi-Human Parsing with Unified Correlation Representation Learning

https://github.com/claudiacuttano/samwise

공식 코드

SAMWISE: Infusing Wisdom in SAM2 for Text-Driven Video Segmentation

https://github.com/clinical-and-translational-imaging-lab/brats-e1d3

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E1D3 U-Net for Brain Tumor Segmentation: Submission to the RSNA-ASNR-MICCAI BraTS 2021 Challenge

https://github.com/clinicaldatascience/tucker-cnn

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Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition

https://github.com/clovaai/SSUL

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SSUL: Semantic Segmentation with Unknown Label for Exemplar-based Class-Incremental Learning

https://github.com/clovaai/deep-text-recognition-benchmark

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What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis

https://github.com/clovaai/synthtiger

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SynthTIGER: Synthetic Text Image GEneratoR Towards Better Text Recognition Models

https://github.com/clusterformer/clusterformer

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ClusterFormer: Clustering As A Universal Visual Learner

https://github.com/cmsflash/global-context-module

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Fast Video Object Segmentation using the Global Context Module

https://github.com/cmu-safari/sasiml

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EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators

https://github.com/cocodataset/panopticapi

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Panoptic Segmentation

https://github.com/cocofeat/devis

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Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated Uncertainty

https://github.com/cocofeat/umis

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Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated Uncertainty

https://github.com/coendevente/nninteractive-slicer

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SlicerNNInteractive: A 3D Slicer extension for nnInteractive

https://github.com/cognitiveaisystems/3dgraphllm

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3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding

https://github.com/coldmanck/RVL-BERT

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Visual Relationship Detection with Visual-Linguistic Knowledge from Multimodal Representations

https://github.com/coldmanck/recovering-unbiased-scene-graphs

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Recovering the Unbiased Scene Graphs from the Biased Ones

https://github.com/colorfulfuture/awesome-trajectory-motion-prediction-papers

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Trajectory Prediction Meets Large Language Models: A Survey

https://github.com/columbia-ai-robotics/BusyBot

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BusyBot: Learning to Interact, Reason, and Plan in a BusyBoard Environment

https://github.com/columbia-ai-robotics/semantic-abstraction

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Semantic Abstraction: Open-World 3D Scene Understanding from 2D Vision-Language Models

https://github.com/comp-syn/comp-syn

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Divergences in Color Perception between Deep Neural Networks and Humans

https://github.com/computational-cell-analytics/medico-sam

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MedicoSAM: Towards foundation models for medical image segmentation

https://github.com/computational-cell-analytics/patho-sam

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Segment Anything for Histopathology

https://github.com/computational-cell-analytics/probabilistic-domain-adaptation

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Probabilistic Domain Adaptation for Biomedical Image Segmentation

https://github.com/computationalpathologygroup/hooknet

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HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images

https://github.com/congvvc/instructseg

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InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language Models

https://github.com/conor-horgan/spectrai

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spectrai: A deep learning framework for spectral data

https://github.com/conscienceli/IterNet

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IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks

https://github.com/constantinpape/cluster_tools

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Leveraging Domain Knowledge to Improve Microscopy Image Segmentation with Lifted Multicuts

https://github.com/cookielee77/DAST

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Domain Adaptive Text Style Transfer

https://github.com/corne00/ddu-net

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DDU-Net: A Domain Decomposition-Based CNN for High-Resolution Image Segmentation on Multiple GPUs

https://github.com/corne00/hires-seg-cnn

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DDU-Net: A Domain Decomposition-Based CNN for High-Resolution Image Segmentation on Multiple GPUs

https://github.com/coslab-kr/tinyseg

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TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems

https://github.com/cp3wan/dformer

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DFormer: Diffusion-guided Transformer for Universal Image Segmentation

https://github.com/crazorback/aadg

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AADG: Automatic Augmentation for Domain Generalization on Retinal Image Segmentation

https://github.com/creatis-myriad/ascent

공식 코드

Extraction of volumetric indices from echocardiography: which deep learning solution for clinical use?

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