Papers with Code 아카이브
2D Object Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/siddiquemu/sct_mcta
공식 코드Tracking Passengers and Baggage Items using Multiple Overhead Cameras at Security Checkpoints
https://github.com/sidiangongyuan/acco
공식 코드Is Discretization Fusion All You Need for Collaborative Perception?
https://github.com/sigma10010/nuclei_cells_det
공식 코드SRPN: similarity-based region proposal networks for nuclei and cells detection in histology images
https://github.com/sigmalabresearch/visnotate
공식 코드https://github.com/simon-lepage/condvit-lrvsf
공식 코드LRVS-Fashion: Extending Visual Search with Referring Instructions
https://github.com/simonklind/nf-gradients
공식 코드https://github.com/simula/Kvasir-VQA
공식 코드https://github.com/sinamalakouti/CDDMSL
공식 코드Semi-Supervised Domain Generalization for Object Detection via Language-Guided Feature Alignment
https://github.com/sinatayebati/radial_mae
공식 코드https://github.com/sindish/unitedwelearn
공식 코드United We Learn Better: Harvesting Learning Improvements From Class Hierarchies Across Tasks
https://github.com/sisl/visionbasedaircraftdaa
공식 코드AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator
https://github.com/sissiw/mutualformer
공식 코드MutualFormer: Multi-Modality Representation Learning via Cross-Diffusion Attention
https://github.com/siyueyu/SCWSSOD
공식 코드Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence
https://github.com/siyueyu/dcfm
공식 코드Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detection
https://github.com/skmhrk1209/VSRD
공식 코드VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object Detection
https://github.com/sky77764/pa-aug.pytorch
공식 코드Part-Aware Data Augmentation for 3D Object Detection in Point Cloud
https://github.com/skyhehe123/msf
공식 코드MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequences
https://github.com/skyhehe123/voxset
공식 코드Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds
https://github.com/skyoux/SemAIM
공식 코드Semantic-Aware Autoregressive Image Modeling for Visual Representation Learning
https://github.com/sldgroup/mobilevig
공식 코드MobileViG: Graph-Based Sparse Attention for Mobile Vision Applications
https://github.com/sldgroup/mobilevigv2
공식 코드https://github.com/slds-lmu/wildlife-experiments
공식 코드Automated wildlife image classification: An active learning tool for ecological applications
https://github.com/slds-lmu/wildlife-ml
공식 코드Automated wildlife image classification: An active learning tool for ecological applications
https://github.com/slerman12/ExplainingInteractions
공식 코드Explaining Local, Global, And Higher-Order Interactions In Deep Learning
https://github.com/slongliu/dab-detr
공식 코드https://github.com/smartbot-pjlab/dort
공식 코드DORT: Modeling Dynamic Objects in Recurrent for Multi-Camera 3D Object Detection and Tracking
https://github.com/smartbot-pjlab/mv-jar
공식 코드MV-JAR: Masked Voxel Jigsaw and Reconstruction for LiDAR-Based Self-Supervised Pre-Training
https://github.com/smartslab/objectRecognitionTopologicalFeatures
공식 코드Visual Object Recognition in Indoor Environments Using Topologically Persistent Features
https://github.com/smcch/brain_tumor_detection_ultrasound
공식 코드https://github.com/smin-hwang/ic-fusion
공식 코드Multispectral Detection Transformer with Infrared-Centric Sensor Fusion
https://github.com/smlc-nysbc/target-vae
공식 코드Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE
https://github.com/snap-stanford/orca
공식 코드https://github.com/snowdusky/dualpolishlearning
공식 코드Mind the Gap: Polishing Pseudo labels for Accurate Semi-supervised Object Detection
https://github.com/snu-drl/drcpo
공식 코드https://github.com/sofmonk/class_agnostic_loss_saliency
공식 코드Class-Agnostic Segmentation Loss and Its Application to Salient Object Detection and Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.