https://github.com/facebookresearch/phosa
공식 코드Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
Papers with Code 아카이브
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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/facebookresearch/projectaria_tools
공식 코드Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine Perception
https://github.com/facebookresearch/uco3d
공식 코드https://github.com/facebookresearch/unbiased-teacher
공식 코드https://github.com/facebookresearch/unsamflow
공식 코드UnSAMFlow: Unsupervised Optical Flow Guided by Segment Anything Model
https://github.com/facebookresearch/vissl
공식 코드Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
https://github.com/facebookresearch/vlpart
공식 코드https://github.com/facebookresearch/votenet
공식 코드https://github.com/facebookresearch/vq2d_cvpr
공식 코드Negative Frames Matter in Egocentric Visual Query 2D Localization
https://github.com/facias914/A-Simple-Detector-is-a-Strong-Tracker
공식 코드https://github.com/fangyi-chen/sqr
공식 코드Enhanced Training of Query-Based Object Detection via Selective Query Recollection
https://github.com/fanq15/FewX
공식 코드Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector
https://github.com/fanq15/GCoNet
공식 코드Group Collaborative Learning for Co-Salient Object Detection
https://github.com/fanyang587/MGL
공식 코드https://github.com/fanyihua0309/friendnet
공식 코드https://github.com/fatemehN/ABBG
공식 코드Adversarial Bounding Boxes Generation (ABBG) Attack against Visual Object Trackers
https://github.com/fatemehN/TrackPGD
공식 코드TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer Trackers
https://github.com/fatemehN/entangled_representation
공식 코드$β$-Multivariational Autoencoder for Entangled Representation Learning in Video Frames
https://github.com/fatemehazimi990/RS2S
공식 코드Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory
https://github.com/fatemehn/reproducibilitystudy
공식 코드Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers
https://github.com/fatemehpesaran310/lpoi
공식 코드LPOI: Listwise Preference Optimization for Vision Language Models
https://github.com/fcakyon/sahi-benchmark
공식 코드Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection
https://github.com/fcdl94/mma
공식 코드Modeling Missing Annotations for Incremental Learning in Object Detection
https://github.com/fcendra/sl3d
공식 코드https://github.com/fcjian/AeDet
공식 코드https://github.com/fcjian/PromptDet
공식 코드PromptDet: Towards Open-vocabulary Detection using Uncurated Images
https://github.com/fcjian/TOOD
공식 코드https://github.com/fcjian/loce
공식 코드Exploring Classification Equilibrium in Long-Tailed Object Detection
https://github.com/fehmikahraman/corrloss
공식 코드Correlation Loss: Enforcing Correlation between Classification and Localization
https://github.com/feiaxyt/Winner_ECCV20_TAO
공식 코드1st Place Solution to ECCV-TAO-2020: Detect and Represent Any Object for Tracking
https://github.com/feichtenhofer/detect-track
공식 코드https://github.com/feipanir/moda
공식 코드https://github.com/feobi1999/tdd
공식 코드Cross Domain Object Detection by Target-Perceived Dual Branch Distillation
https://github.com/ferry-li/si-sod
공식 코드https://github.com/fgiuliari/spatialcommonsensegraph-dataset
공식 코드Spatial Commonsense Graph for Object Localisation in Partial Scenes
https://github.com/fh2019ustc/polysnake
공식 코드Recurrent Generic Contour-based Instance Segmentation with Progressive Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.