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/e-lab/pytorch-linknet

LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation

https://github.com/e9190712/vessel_segmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/eagleadelaide/sdc-loss

We Care Each Pixel: Calibrating on Medical Segmentation Model

https://github.com/earth-insights/ClassTrans

CascadePSP: Toward Class-Agnostic and Very High-Resolution Segmentation via Global and Local Refinement

https://github.com/ebagdasa/backdoors101

Multi-Task Learning as Multi-Objective Optimization

https://github.com/eceo-epfl/scaleprotoseg

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

https://github.com/eddiebarry/SingleShotDetector

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/elliottwu/sorderender

PointRend: Image Segmentation as Rendering

https://github.com/elonashatri/pitch_mask_rcnn

Mask R-CNN

https://github.com/emsalinha/videosum-eval

Rethinking the Evaluation of Video Summaries

https://github.com/enot-autodl/lpcv-2023

UAVid: A Semantic Segmentation Dataset for UAV Imagery

https://github.com/ensta-u2is/deeplabv3plus-muad-pytorch

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/ericoldgren/kex---ct-reconstruction

2DeteCT -- A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning

https://github.com/eriklindernoren/Keras-GAN

Boundary-Seeking Generative Adversarial Networks

https://github.com/eriklindernoren/PyTorch-GAN

Boundary-Seeking Generative Adversarial Networks

https://github.com/espressif/esp-who

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/ethanhou99/ml_learn

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/ethz-asl/pvlff

Neural Implicit Vision-Language Feature Fields

https://github.com/etrommer/dcsr

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/eunki7/flask-deeplearning-service-demo

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/evaristr/py-faster_rcnn

Mask R-CNN

https://github.com/facebookresearch/MultipleAttributeTextRewriting

Multiple-Attribute Text Style Transfer

https://github.com/facebookresearch/SegmPred

Predicting Deeper into the Future of Semantic Segmentation

https://github.com/facebookresearch/TensorComprehensions

Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

https://github.com/facebookresearch/detectron

Mask R-CNN

https://github.com/facebookresearch/detectron2

Mask R-CNN

https://github.com/facebookresearch/habitat-api/tree/master/habitat_baselines/rl/ddppo

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames

https://github.com/facebookresearch/maskrcnn-benchmark

Mask R-CNN

https://github.com/facebookresearch/sapiens

Sapiens: Foundation for Human Vision Models

https://github.com/faroukmokhtar/ImageSegmentationPASCAL

Image Segmentation Using Deep Learning: A Survey

https://github.com/fcdl94/MiB

Modeling the Background for Incremental Learning in Semantic Segmentation

https://github.com/fdac18/ForensicImages

Mask R-CNN

https://github.com/federicopozzi33/MobileOne-PyTorch

MobileOne: An Improved One millisecond Mobile Backbone

https://github.com/feevos/resuneta

ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data

https://github.com/feinanshan/TDNet

Temporally Distributed Networks for Fast Video Semantic Segmentation

https://github.com/fenghetan9/hyspark

Slide-SAM: Medical SAM Meets Sliding Window

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