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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ocpm/ocpa
공식 코드A Framework for Extracting and Encoding Features from Object-Centric Event Data
https://github.com/olly-styles/Multiple-Object-Forecasting
공식 코드Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments
https://github.com/om-ai-lab/OmDet
공식 코드OmDet: Large-scale vision-language multi-dataset pre-training with multimodal detection network
https://github.com/omar9008-eng/Object-Detection-Tracking-2025
공식 코드https://github.com/ombretta/humans-vs-detectors
공식 코드Aligning Object Detector Bounding Boxes with Human Preference
https://github.com/omidmnezami/pick-object-attack
공식 코드Pick-Object-Attack: Type-Specific Adversarial Attack for Object Detection
https://github.com/ondrejba/action_attention_iclr_22
공식 코드https://github.com/onmyoji-xiao/AS3D
공식 코드https://github.com/oooolga/Ctrl-V
공식 코드Ctrl-V: Higher Fidelity Video Generation with Bounding-Box Controlled Object Motion
https://github.com/open-mmlab/OpenPCDet
공식 코드PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
https://github.com/open-mmlab/mmagic/tree/main/projects/powerpaint
공식 코드A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting
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/mmdetection3d
공식 코드Exploring Data Augmentation for Multi-Modality 3D Object Detection
https://github.com/open-mmlab/mmrotate
공식 코드MMRotate: A Rotated Object Detection Benchmark using PyTorch
https://github.com/open-mmlab/mmtracking
공식 코드https://github.com/openat25/hiptrack-mls
공식 코드https://github.com/opencodegithub/h-dcpt
공식 코드https://github.com/opendr-eu/opendr
공식 코드VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images
https://github.com/opendrivelab/bevperception-survey-recipe
공식 코드Geometric-aware Pretraining for Vision-centric 3D Object Detection
https://github.com/opengvlab/ego4d-eccv2022-solutions
공식 코드InternVideo-Ego4D: A Pack of Champion Solutions to Ego4D Challenges
https://github.com/opengvlab/mutr
공식 코드Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation
https://github.com/opennlplab/avs-bidirectional
공식 코드Improving Audio-Visual Segmentation with Bidirectional Generation
https://github.com/openrobotlab/egohod
공식 코드Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation Learning
https://github.com/openrobotlab/pointllm
공식 코드PointLLM: Empowering Large Language Models to Understand Point Clouds
https://github.com/openrobotlab/vlm-grounder
공식 코드https://github.com/opipari/clearpose
공식 코드ClearPose: Large-scale Transparent Object Dataset and Benchmark
https://github.com/oreochocolate/lain
공식 코드https://github.com/orhir/PoseAnything
공식 코드A Graph-Based Approach for Category-Agnostic Pose Estimation
https://github.com/orrzohar/prob
공식 코드PROB: Probabilistic Objectness for Open World Object Detection
https://github.com/oskyhn/DelftBikes
공식 코드Hallucination In Object Detection -- A Study In Visual Part Verification
https://github.com/oskyhn/detectors-context
공식 코드https://github.com/osvai/noah
공식 코드NOAH: Learning Pairwise Object Category Attentions for Image Classification
https://github.com/otaheri/GOAL
공식 코드GOAL: Generating 4D Whole-Body Motion for Hand-Object Grasping
https://github.com/otaheri/GRAB
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.