Papers with Code 아카이브
2D Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/coo1sea/ovt-b-dataset
공식 코드OVT-B: A New Large-Scale Benchmark for Open-Vocabulary Multi-Object Tracking
https://github.com/coolbay/Dr2Net
공식 코드Dr$^2$Net: Dynamic Reversible Dual-Residual Networks for Memory-Efficient Finetuning
https://github.com/coperception/robosac
공식 코드Among Us: Adversarially Robust Collaborative Perception by Consensus
https://github.com/correr-zhou/disco
공식 코드Distribution-Aware Calibration for Object Detection with Noisy Bounding Boxes
https://github.com/cosanlab/py-feat
공식 코드https://github.com/cps-research-group/cps-ntu-public
공식 코드Demo Abstract: Real-Time Out-of-Distribution Detection on a Mobile Robot
https://github.com/cps-tuwien/learning_human_attention
공식 코드Enhancing Robot Learning through Learned Human-Attention Feature Maps
https://github.com/craftGBD/craftGBD
공식 코드https://github.com/craston/object_detection_cib
공식 코드Class Imbalance in Object Detection: An Experimental Diagnosis and Study of Mitigation Strategies
https://github.com/crusnic-corp/BN-DRISHTI
공식 코드https://github.com/cs-chan/Exclusively-Dark-Image-Dataset
공식 코드Getting to Know Low-light Images with The Exclusively Dark Dataset
https://github.com/csdllab/mca
공식 코드https://github.com/cshan-github/tonguesam
공식 코드TongueSAM: An Universal Tongue Segmentation Model Based on SAM with Zero-Shot
https://github.com/csiplab/ebad
공식 코드https://github.com/csiplab/mmsformer
공식 코드MMSFormer: Multimodal Transformer for Material and Semantic Segmentation
https://github.com/csiro-robotics/fn_mechanisms
공식 코드What's in the Black Box? The False Negative Mechanisms Inside Object Detectors
https://github.com/cskkxjk/mononerd
공식 코드MonoNeRD: NeRF-like Representations for Monocular 3D Object Detection
https://github.com/csl-ku/valo
공식 코드VALO: A Versatile Anytime Framework for LiDAR-based Object Detection Deep Neural Networks
https://github.com/csuhan/ReDet
공식 코드ReDet: A Rotation-equivariant Detector for Aerial Object Detection
https://github.com/csuhan/opendet2
공식 코드Expanding Low-Density Latent Regions for Open-Set Object Detection
https://github.com/csuhan/s2anet
공식 코드https://github.com/csuhan/vfa
공식 코드Few-Shot Object Detection via Variational Feature Aggregation
https://github.com/csuvis/BarchartReverseEngineering
공식 코드https://github.com/csysi/fsel
공식 코드Frequency-Spatial Entanglement Learning for Camouflaged Object Detection
https://github.com/csysi/glconet
공식 코드GLCONet: Learning Multi-source Perception Representation for Camouflaged Object Detection
https://github.com/csysi/udcnet
공식 코드United Domain Cognition Network for Salient Object Detection in Optical Remote Sensing Images
https://github.com/cszzshi/SimD
공식 코드Similarity Distance-Based Label Assignment for Tiny Object Detection
https://github.com/ctu-vras/pcl-augmentation
공식 코드https://github.com/ctu-vras/t-concord3d
공식 코드Teachers in concordance for pseudo-labeling of 3D sequential data
https://github.com/ctuning/cbench
공식 코드https://github.com/cuibaby/dpk
공식 코드Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation
https://github.com/cuiziteng/eccv_aeris
공식 코드https://github.com/cuiziteng/iccv_maet
공식 코드Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection
https://github.com/cuiziteng/illumination-adaptive-transformer
공식 코드https://github.com/cuiziteng/maet
공식 코드Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.