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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dingmyu/D4LCN
공식 코드Learning Depth-Guided Convolutions for Monocular 3D Object Detection
https://github.com/dingmyu/davit
공식 코드https://github.com/dingmyu/doubly-robust-self-training
공식 코드https://github.com/dingsheng-ong/ipr-gan
공식 코드Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack
https://github.com/dipayan1109033/edu-video-visual-detection
공식 코드https://github.com/dipayan1109033/lvvo_dataset
공식 코드https://github.com/dirtyharrylyl/hake-ava
공식 코드Discovering A Variety of Objects in Spatio-Temporal Human-Object Interactions
https://github.com/disen-hu/fasterrcnn_fpn_dcn
공식 코드https://github.com/diux-xview/xview3-reference
공식 코드xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery
https://github.com/divadi/detmatch
공식 코드DetMatch: Two Teachers are Better Than One for Joint 2D and 3D Semi-Supervised Object Detection
https://github.com/divadi/solofusion
공식 코드Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
https://github.com/divelab/dilated
공식 코드https://github.com/djamahl99/findnpropagate
공식 코드Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban Environments
https://github.com/djghosh13/geneval
공식 코드GenEval: An Object-Focused Framework for Evaluating Text-to-Image Alignment
https://github.com/djiajunustc/H-23D_R-CNN
공식 코드From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object Detection
https://github.com/djiajunustc/Voxel-R-CNN
공식 코드Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
https://github.com/djning/see_beyond_seeing
공식 코드Robust 3D Object Detection from LiDAR-Radar Point Clouds via Cross-Modal Feature Augmentation
https://github.com/djordjened92/yudo
공식 코드https://github.com/dk-liang/unifuture
공식 코드https://github.com/dkadish/Style-Transfer-for-Object-Detection-in-Art
공식 코드Improving Object Detection in Art Images Using Only Style Transfer
https://github.com/dkoguciuk/ensemble_learning_for_point_clouds
공식 코드3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models
https://github.com/dkxocl/rosseta
공식 코드Continual Object Detection via Prototypical Task Correlation Guided Gating Mechanism
https://github.com/dlgroupuoft/calpric
공식 코드https://github.com/dliu5812/ddf
공식 코드Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement
https://github.com/dlr-mi/utrack
공식 코드https://github.com/dlut-dimt/Realworld-Underwater-Image-Enhancement-RUIE-Benchmark
공식 코드Real-world Underwater Enhancement: Challenges, Benchmarks, and Solutions
https://github.com/dlut-dimt/tardal
공식 코드https://github.com/dmlc/gluon-cv
공식 코드Bag of Tricks for Image Classification with Convolutional Neural Networks
https://github.com/dmtjepa/dmtjepa
공식 코드DMT-JEPA: Discriminative Masked Targets for Joint-Embedding Predictive Architecture
https://github.com/docf/multispectral-object-detection
공식 코드Cross-Modality Fusion Transformer for Multispectral Object Detection
https://github.com/doem97/deblora
공식 코드Learning De-Biased Representations for Remote-Sensing Imagery
https://github.com/dolphin0104/CFMDGAN
공식 코드https://github.com/dongchen06/scooterdet
공식 코드Performance Evaluation of Real-Time Object Detection for Electric Scooters
https://github.com/dongfang-steven-yang/faraway-frustum
공식 코드Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detection using Fusion
https://github.com/donggong1/learn-optimizer-rgdn
공식 코드Learning Deep Gradient Descent Optimization for Image Deconvolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.