Papers with Code 아카이브

Semantic Segmentation

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전체 기법전체 데이터셋

하위 태스크

29

평가표

150

보존된 평가 기록

1,918

코드

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

https://github.com/tduboudi/IAMPS2019-Procedural-Fruit-Tree-Rendering-Framework

공식 코드

Toward a Procedural Fruit Tree Rendering Framework for Image Analysis

https://github.com/techmn/cosnet

공식 코드

COSNet: A Novel Semantic Segmentation Network using Enhanced Boundaries in Cluttered Scenes

https://github.com/techmn/fanet

공식 코드

FANet: Feature Amplification Network for Semantic Segmentation in Cluttered Background

https://github.com/teddykoker/u-noise

공식 코드

U-Noise: Learnable Noise Masks for Interpretable Image Segmentation

https://github.com/tencentarc/conmim

공식 코드

Masked Image Modeling with Denoising Contrast

https://github.com/tencentarc/sgat4pass

공식 코드

SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation

https://github.com/tencentyouturesearch/highlightdetection-clc

공식 코드

Collaborative Noisy Label Cleaner: Learning Scene-aware Trailers for Multi-modal Highlight Detection in Movies

https://github.com/tencentyouturesearch/visualrecognition-nommer

공식 코드

NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition

https://github.com/tennine2077/pdfnet

공식 코드

Patch-Depth Fusion: Dichotomous Image Segmentation via Fine-Grained Patch Strategy and Depth Integrity-Prior

https://github.com/tensorflow/models

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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/deepmac.md

공식 코드

The surprising impact of mask-head architecture on novel class segmentation

https://github.com/tensorflow/models/tree/master/official/projects/mosaic

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MOSAIC: Mobile Segmentation via decoding Aggregated Information and encoded Context

https://github.com/tensorflow/models/tree/master/official/vision/beta/projects/deepmac_maskrcnn

공식 코드

The surprising impact of mask-head architecture on novel class segmentation

https://github.com/tensorflow/tpu

공식 코드

Simple Training Strategies and Model Scaling for Object Detection

https://github.com/tensorflow/tpu/tree/641c1ac6e26ed788327b973582cbfa297d7d31e7/models/official/detection/projects/openseg

공식 코드

Scaling Open-Vocabulary Image Segmentation with Image-Level Labels

https://github.com/tensorflow/tpu/tree/master/models/official/detection/projects/copy_paste

공식 코드

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

https://github.com/tensorflow/tpu/tree/master/models/official/detection/projects/fashionpedia

공식 코드

Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset

https://github.com/terminal-k/mambamos

공식 코드

MambaMOS: LiDAR-based 3D Moving Object Segmentation with Motion-aware State Space Model

https://github.com/ternaus/TernausNet

공식 코드

TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation

https://github.com/ternaus/TernausNetV2

공식 코드

TernausNetV2: Fully Convolutional Network for Instance Segmentation

https://github.com/ternaus/robot-surgery-segmentation

공식 코드

Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning

https://github.com/teryzh/reconstruction-ngsim-trajectory-with-dmd-and-res_unet_plus

공식 코드

Spatial-Temporal Map Vehicle Trajectory Detection Using Dynamic Mode Decomposition and Res-UNet+ Neural Networks

https://github.com/tfboys-lzz/mpscl

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Margin Preserving Self-paced Contrastive Learning Towards Domain Adaptation for Medical Image Segmentation

https://github.com/tfonta/semantic-vae

공식 코드

Automatic Generation of Semantic Parts for Face Image Synthesis

https://github.com/tfzhou/ContrastiveSeg

공식 코드

Exploring Cross-Image Pixel Contrast for Semantic Segmentation

https://github.com/tfzhou/MATNet

공식 코드

Motion-Attentive Transition for Zero-Shot Video Object Segmentation

https://github.com/tfzhou/MG-HumanParsing

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Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing

https://github.com/tfzhou/protoseg

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Rethinking Semantic Segmentation: A Prototype View

https://github.com/tfzhou/vs-survey

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A Survey on Deep Learning Technique for Video Segmentation

https://github.com/tgrex6/unetvl

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UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM

https://github.com/th2l/Agriculture-Vision-Segmentation

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The 1st Agriculture-Vision Challenge: Methods and Results

https://github.com/th2l/Eye_VR_Segmentation

공식 코드

Eye Semantic Segmentation with a Lightweight Model

https://github.com/thangvubk/softgroup

공식 코드

SoftGroup for 3D Instance Segmentation on Point Clouds

https://github.com/thanos-db/fullyconvolutionaltransformer

공식 코드

The Fully Convolutional Transformer for Medical Image Segmentation

https://github.com/theFoxofSky/ddf

공식 코드

Decoupled Dynamic Filter Networks

https://github.com/theeighthday/co-teaching

공식 코드

Co-Teaching for Unsupervised Domain Adaptation and Expansion

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