Papers with Code 아카이브

3D Instance Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

9

보존된 평가 기록

79

코드

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

https://github.com/lixiaolei1982/DenseNet-base-Mask-RCNN-for-Human-Pose-Estimation

Mask R-CNN

https://github.com/longcw/roialign.pytorch

Mask R-CNN

https://github.com/louisyuzhe/car-damage-detector

Mask R-CNN

https://github.com/ls5122/mask-rcnn

Mask R-CNN

https://github.com/lucylow/salty-wet-man

Mask R-CNN

https://github.com/lukoucky/image_recommendation

Mask R-CNN

https://github.com/luost26/diffusion-point-cloud

PointCNN: Convolution On $\mathcal{X}$-Transformed Points

https://github.com/lyqcom/3d-unet

3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

https://github.com/manideep03/Brain-Tumor-Segmentation

3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

https://github.com/maxfrei750/DeepParticleNet

Mask R-CNN

https://github.com/maxfrei750/FibeR-CNN

Mask R-CNN

https://github.com/miaohua1982/simple_fasterrcnn_pytorch

Mask R-CNN

https://github.com/mic-dkfz/medicaldetectiontoolkit

Mask R-CNN

https://github.com/mindspore-ai/models/tree/master/official/cv/maskrcnn

Mask R-CNN

https://github.com/mirzaevinom/data_science_bowl_2018

Mask R-CNN

https://github.com/mlf-core/liver-ct-segmentation

3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

https://github.com/mstfakts/building-detection-maskrcnn

Mask R-CNN

https://github.com/multimodallearning/pytorch-mask-rcnn

Mask R-CNN

https://github.com/muyistarsky/MaskRCNN

Mask R-CNN

https://github.com/nicolas-chaulet/torch-points3d

PointCNN: Convolution On $\mathcal{X}$-Transformed Points

https://github.com/nikhithakarennagari/1311

Mask R-CNN

https://github.com/nikhithakarennagari/Git

Mask R-CNN

https://github.com/noelcodes/Mask_RCNN

Mask R-CNN

https://github.com/o-evgeny/MRCNN_DeepFashion2

Mask R-CNN

https://github.com/octree-nn/ocnn-pytorch

PointCNN: Convolution On $\mathcal{X}$-Transformed Points

https://github.com/oneformer3d/oneformer3d

OneFormer3D: One Transformer for Unified Point Cloud Segmentation

https://github.com/open-edge-platform/geti

Mask R-CNN

https://github.com/open-edge-platform/training_extensions

Mask R-CNN

https://github.com/paradisetechsoftsolutions/Deep-learning-model-using-Mask-R-CNN-for-predicting-AC-remote

Mask R-CNN

https://github.com/phtruongan/py-faster-rcnn-docker

Mask R-CNN

https://github.com/phykn/film-defect-detection

Mask R-CNN

https://github.com/pj1920/mask-r-cnn

Mask R-CNN

https://github.com/polospeter/TensorFlow-Advanced-Techniques-Specialization

Mask R-CNN

https://github.com/pvdhove/owl-mask-rcnn

Mask R-CNN

https://github.com/pyg-team/pytorch_geometric

PointCNN: Convolution On $\mathcal{X}$-Transformed Points

https://github.com/qilei123/pyfasterrcnn

Mask R-CNN

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