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/sunhui1234/haha
https://github.com/sunqiangxtcsun/faster-rcnn
https://github.com/sunutf/TSM
https://github.com/suvasis/birdnet2cs231n
https://github.com/suyukun666/CDA
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations
https://github.com/tanmaypandey7/wheat-detection
https://github.com/tarun-munjal/mmdetection
https://github.com/tch/pointcnn
https://github.com/tea1528/Non-Local-NN-Pytorch
https://github.com/tencentyouturesearch/personretrieval-ivt
https://github.com/tensorflow/models/tree/master/official/projects/panoptic
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
https://github.com/tensorflow/models/tree/master/official/vision
https://github.com/tensorflow/models/tree/master/research/object_detection
The surprising impact of mask-head architecture on novel class segmentation
https://github.com/tensorflow/tpu/tree/master/models/official/detection
ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors
https://github.com/tensorpack/tensorpack/tree/master/examples/FasterRCNN
https://github.com/texasinstruments/edgeai-yolov5
https://github.com/texasinstruments/edgeai-yolox
https://github.com/thangvubk/SCNet
https://github.com/theodorakontogianni/interobject3d
https://github.com/theostoican/Guided-Research/blob/main/finetuning_odin_resnet.ipynb
https://github.com/thepooons/melanoma-comp-2020
https://github.com/thomasslloyd/FitSpatial
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/thoughtmachines/Human-Pose-Estimation-using-HRNets
Deep High-Resolution Representation Learning for Human Pose Estimation
https://github.com/thoughtworks-hpc/PINetTensorrt
Key Points Estimation and Point Instance Segmentation Approach for Lane Detection
https://github.com/thunlp/pevl
MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding
https://github.com/tianchiVideoSeg/mmdetection
https://github.com/tianhai123/mmdetection
https://github.com/tianyaoZhang/DeeCamp
https://github.com/timothyn617/watershed-transform
https://github.com/tinymilky/RSANet
https://github.com/tonysy/PyAction
https://github.com/torchjd/torchjd
https://github.com/towhee-io/towhee
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/trhieu310/customDataset
https://github.com/tryolabs/luminoth
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.