Object Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/turoad/scaloss
공식 코드SCALoss: Side and Corner Aligned Loss for Bounding Box Regression
https://github.com/tusen-ai/mv2d
공식 코드Object as Query: Lifting any 2D Object Detector to 3D Detection
https://github.com/tusen-ai/sst
공식 코드https://github.com/tusimple/centerformer
공식 코드CenterFormer: Center-based Transformer for 3D Object Detection
https://github.com/tusimple/simpledet
공식 코드https://github.com/tusimple/sst
공식 코드Embracing Single Stride 3D Object Detector with Sparse Transformer
https://github.com/tustailab/hmpnet
공식 코드https://github.com/twangnh/Distilling-Object-Detectors
공식 코드Distilling Object Detectors with Fine-grained Feature Imitation
https://github.com/twangnh/SimCal
공식 코드https://github.com/twangnh/pnp-detr
공식 코드PnP-DETR: Towards Efficient Visual Analysis with Transformers
https://github.com/tydpan/NorCal
공식 코드On Model Calibration for Long-Tailed Object Detection and Instance Segmentation
https://github.com/tydpan/gpc
공식 코드Pre-Training LiDAR-Based 3D Object Detectors Through Colorization
https://github.com/tyomj/product_detection
공식 코드https://github.com/tztztztztz/eql.detectron2
공식 코드https://github.com/tztztztztz/eqlv2
공식 코드Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection
https://github.com/ubamba98/EAD2020
공식 코드Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection
https://github.com/uber-research/permute-quantize-finetune
공식 코드Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks
https://github.com/uber/sbnet
공식 코드https://github.com/ucas-gyx/youtube-gdd
공식 코드YouTube-GDD: A challenging gun detection dataset with rich contextual information
https://github.com/ucas-vg/TinyBenchmark
공식 코드https://github.com/ucas-vg/p2bnet
공식 코드Point-to-Box Network for Accurate Object Detection via Single Point Supervision
https://github.com/ucas-vg/pointtinybenchmark
공식 코드Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes
https://github.com/ucbdrive/few-shot-object-detection
공식 코드https://github.com/ucla-mobility/v2v4real
공식 코드V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception
https://github.com/ucr-robotics/citrus-farm-dataset
공식 코드Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms
https://github.com/uddd821/hv-bev
공식 코드HV-BEV: Decoupling Horizontal and Vertical Feature Sampling for Multi-View 3D Object Detection
https://github.com/uestc-nnlab/tridos
공식 코드https://github.com/uestc-nnlab/wecol
공식 코드https://github.com/uf-aiaos/shinyanimalcv
공식 코드https://github.com/ufukertenli/streamdeq-code
공식 코드https://github.com/umd-fire-coml/kitti-orientation-learning
공식 코드SoK: Vehicle Orientation Representations for Deep Rotation Estimation
https://github.com/unibwtas/yolopoint
공식 코드https://github.com/unique-chan/nbbox
공식 코드NBBOX: Noisy Bounding Box Improves Remote Sensing Object Detection
https://github.com/uobinxiao/SparseTableDet
공식 코드https://github.com/update-for-integrated-business-ai/coru
공식 코드CORU: Comprehensive Post-OCR Parsing and Receipt Understanding Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.