https://github.com/nullmax-vision/simpb
공식 코드SimPB: A Single Model for 2D and 3D Object Detection from Multiple Cameras
Papers with Code 아카이브
Object Detection
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nust-machine-intelligence-laboratory/pkinet
공식 코드https://github.com/nutonomy/nuscenes-devkit
공식 코드https://github.com/nutonomy/second.pytorch
공식 코드PointPillars: Fast Encoders for Object Detection from Point Clouds
https://github.com/nv-tlabs/cosmos-drive-dreams
공식 코드Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
https://github.com/nvakhoa/mpad
공식 코드Multi-Perspective Data Augmentation for Few-shot Object Detection
https://github.com/nvlabs/al-mdn
공식 코드Active Learning for Deep Object Detection via Probabilistic Modeling
https://github.com/nvlabs/fan
공식 코드https://github.com/nvlabs/freesolo
공식 코드https://github.com/nvlabs/gcvit
공식 코드https://github.com/nvlabs/mambavision
공식 코드https://github.com/nvlabs/radio
공식 코드AM-RADIO: Agglomerative Vision Foundation Model -- Reduce All Domains Into One
https://github.com/nvsclub/shotspeedestimation
공식 코드https://github.com/o937-blip/simir
공식 코드https://github.com/obss/sahi
공식 코드Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection
https://github.com/ocean146/SimROD
공식 코드SimROD: A Simple Baseline for Raw Object Detection with Global and Local Enhancements
https://github.com/ocnflag/point2seq
공식 코드https://github.com/octree-nn/octformer
공식 코드https://github.com/oiplab-dut/mfnet
공식 코드MFNet: Multi-filter Directive Network for Weakly Supervised Salient Object Detection
https://github.com/ok-robot/ok-robot
공식 코드OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics
https://github.com/okojoalg/dfformer
공식 코드https://github.com/okojoalg/raft-mlp
공식 코드RaftMLP: How Much Can Be Done Without Attention and with Less Spatial Locality?
https://github.com/oliverrensu/deepmim
공식 코드https://github.com/om-ai-lab/OmDet
공식 코드OmDet: Large-scale vision-language multi-dataset pre-training with multimodal detection network
https://github.com/om-ai-lab/groundvlp
공식 코드https://github.com/om-ai-lab/ovdeval
공식 코드https://github.com/om-ai-lab/vlm-r1
공식 코드VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
https://github.com/omar9008-eng/Object-Detection-Tracking-2025
공식 코드https://github.com/omidmnezami/pick-object-attack
공식 코드Pick-Object-Attack: Type-Specific Adversarial Attack for Object Detection
https://github.com/omni-us/research-dataset-sGMB
공식 코드A Neural Model for Text Localization, Transcription and Named Entity Recognition in Full Pages
https://github.com/omni-us/research-e2e-pagereader
공식 코드A Neural Model for Text Localization, Transcription and Named Entity Recognition in Full Pages
https://github.com/open-air-sun/pq-transformer
공식 코드PQ-Transformer: Jointly Parsing 3D Objects and Layouts from Point Clouds
https://github.com/open-mmlab/OpenPCDet
공식 코드PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
https://github.com/open-mmlab/mmdetection
공식 코드https://github.com/open-mmlab/mmdetection/tree/3.x/configs/rtmdet
공식 코드RTMDet: An Empirical Study of Designing Real-Time Object Detectors
https://github.com/open-mmlab/mmdetection/tree/master/configs/groie
공식 코드A novel Region of Interest Extraction Layer for Instance Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.