https://github.com/facebookresearch/DomainBed
SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark
Papers with Code 아카이브
Instance Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 17
- 평가표
- 36
- 보존된 평가 기록
- 338
Instance Segmentation is a computer vision task that involves identifying and separating individual objects within an image, including detecting the boundaries of each object and assigning a unique label to each object. The goal of instance segmentation is to produce a pixel-wise segmentation map of the image, where each pixel is assigned to a specific object instance.
Image Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/facebookresearch/detectron
https://github.com/facebookresearch/detectron2/tree/master/projects/Panoptic-DeepLab
https://github.com/facebookresearch/dino
https://github.com/facebookresearch/instpred
Predicting Future Instance Segmentation by Forecasting Convolutional Features
https://github.com/facebookresearch/multimodal
MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding
https://github.com/facebookresearch/multipathnet
https://github.com/facebookresearch/vissl
https://github.com/facebookresearch/xformers
https://github.com/fangyi-chen/sqr
https://github.com/fanzhemeng/yolact_edge-myver
https://github.com/fastestimator/fastestimator/blob/master/apphub/instance_segmentation/solov2/solov2_tf.py
https://github.com/fdac18/ForensicImages
https://github.com/fehmikahraman/mmdetection
https://github.com/feiyuhuahuo/Yolact_minimal
https://github.com/feng-lab/mmdetection
https://github.com/fepegar/unet
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
https://github.com/ferna11i/detectron2_ResNeST
https://github.com/finepix/small_object_augmentation
https://github.com/fiveai/saod
https://github.com/floatingstarZ/loc_cls_exp
https://github.com/flyfly666/mmdetection2.18.1
https://github.com/flyingTan/QuantMmdetection
https://github.com/flytocc/CycleMLP-paddle
https://github.com/flytocc/PaddleClas
https://github.com/fogfog2/packnet
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/fountain-y/ranksortloss
Rank & Sort Loss for Object Detection and Instance Segmentation
https://github.com/francisengelmann/3D-MPA
3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation
https://github.com/frank-xwang/TBC-TiedBlockConvolution
Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters
https://github.com/franknb/Self-attention-DCGAN
https://github.com/frgfm/Holocron
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
https://github.com/fsafe/Capstone
https://github.com/fujianhai/mmdet-king
https://github.com/fupiao1998/res2net-keras
https://github.com/fuxiao0719/panopticnerf
Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentation
https://github.com/fzi-forschungszentrum-informatik/mrf
SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground Truth
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.