Papers with Code 아카이브
Object
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Replace the cat with a British Shorthair cat of the breed with bulging yellow eyes
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/balancap/SSD-Tensorflow
https://github.com/balshersingh10/Object-Recognition
https://github.com/banben/maskrcnn-benchmark
https://github.com/baneitixiaomai/joint_sod_cod
Uncertainty-aware Joint Salient Object and Camouflaged Object Detection
https://github.com/baodi23/hourglass-facekeypoints-detection
https://github.com/bareblackfoot/IDNet
Learning Instance-Aware Object Detection Using Determinantal Point Processes
https://github.com/bareblackfoot/faster-rcnn.selection
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/bareblackfoot/lddp-tf-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/barisbatuhan/dass_det_inference
https://github.com/barisbatuhan/dass_detector
https://github.com/barmayo/spatial_attention
https://github.com/basaltzhang/maskrcnn-benchmark
https://github.com/basile-bron/Artificial-Intelligence-Bible
https://github.com/basile-bron/Artificial-Intelligence-Lexical
https://github.com/basilevh/object-discovery-cp-gan
https://github.com/bayesian-object-tracking/dbot
https://github.com/bcmi/ObjectStitch-Image-Composition
Making Images Real Again: A Comprehensive Survey on Deep Image Composition
https://github.com/bcmi/TopNet-Object-Placement
https://github.com/bcmi/controlcom-image-composition
Making Images Real Again: A Comprehensive Survey on Deep Image Composition
https://github.com/bcmi/phdnet-painterly-image-harmonization
https://github.com/bdsaglam/torch-scae
https://github.com/beapc18/AffordanceNet
AffordanceNet: An End-to-End Deep Learning Approach for Object Affordance Detection
https://github.com/beassssry/U
https://github.com/becauseofAI/DetNet-Keras
https://github.com/bellekci/Towards-Realtime-MOT-windows-py37
https://github.com/beltransen/lidar_bev
BirdNet: a 3D Object Detection Framework from LiDAR information
https://github.com/ben0110/Frustum_pointnet_2D
https://github.com/ben0110/Radar-Pointnet-PARA
https://github.com/ben0110/frustum-pointnets_RSC_RADAR_fil_PC_batch_para
https://github.com/benenzhu/version0.3-scae
https://github.com/benihime91/pytorch_retinanet
https://github.com/benjaminrwilson/inequity-release
https://github.com/benjamintli/darknet-gun-detector
https://github.com/benjamintli/training-results-azure
https://github.com/benywon/ChiQA
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.