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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/RalphMao/PatchNet
공식 코드PatchNet -- Short-range Template Matching for Efficient Video Processing
https://github.com/RalphMao/VMetrics
공식 코드A Delay Metric for Video Object Detection: What Average Precision Fails to Tell
https://github.com/RaoUmer/ISRResCNet
공식 코드Deep Iterative Residual Convolutional Network for Single Image Super-Resolution
https://github.com/RaoUmer/SRResCGAN
공식 코드Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution
https://github.com/RaoUmer/SRResCycGAN
공식 코드Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution
https://github.com/Rishit-dagli/CPPE-Dataset
공식 코드https://github.com/RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection
공식 코드Radar+RGB Attentive Fusion for Robust Object Detection in Autonomous Vehicles
https://github.com/Robert-Mar/VFA
공식 코드https://github.com/Rock-100/MonoDet
공식 코드Geometry-based Distance Decomposition for Monocular 3D Object Detection
https://github.com/Rokken-lab6/Failure-Analysis-and-Model-Repairment
공식 코드A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging
https://github.com/Ruiyang-061X/UA3D
공식 코드Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection
https://github.com/RunpeiDong/DGMS
공식 코드Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks
https://github.com/RuoyuChen10/CCL-FSOD
공식 코드https://github.com/RyanXLi/OneshotDet
공식 코드https://github.com/SALT-NLP/LLaVAR
공식 코드LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding
https://github.com/SHI-Labs/Convolutional-MLPs
공식 코드https://github.com/SHI-Labs/Cross-Scale-Non-Local-Attention
공식 코드Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
https://github.com/SHI-Labs/Neighborhood-Attention-Transformer
공식 코드https://github.com/SHI-Labs/Pseudo-IoU-for-Anchor-Free-Object-Detection
공식 코드Pseudo-IoU: Improving Label Assignment in Anchor-Free Object Detection
https://github.com/SIAnalytics/RHINO
공식 코드Hausdorff Distance Matching with Adaptive Query Denoising for Rotated Detection Transformer
https://github.com/SJTU-Det/R3Det_Tensorflow
공식 코드R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
https://github.com/SJTU-LuHe/TransVOD
공식 코드End-to-End Video Object Detection with Spatial-Temporal Transformers
https://github.com/SJTU-Thinklab-Det/DOTA-DOAI
공식 코드https://github.com/SJTU-Thinklab-Det/OHDet_Tensorflow
공식 코드On the Arbitrary-Oriented Object Detection: Classification based Approaches Revisited
https://github.com/SJTU-Thinklab-Det/r3det-on-mmdetection
공식 코드R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
https://github.com/SLDGroup/GreedyViG
공식 코드GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs
https://github.com/SLWZwaard/DMT
공식 코드https://github.com/SS47816/AGI-Elo
공식 코드https://github.com/SSEditor/SSEditor
공식 코드SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model
https://github.com/STVIR/Grid-R-CNN
공식 코드https://github.com/SYangDong/tse-t
공식 코드Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection
https://github.com/Sagarika-Singh-99/indonesian_manhwa_translation
공식 코드Crossing Language Borders: A Pipeline for Indonesian Manhwa Translation
https://github.com/SaliencyMix/SaliencyMix
공식 코드SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
https://github.com/Scalsol/RepPointsV2
공식 코드RepPoints V2: Verification Meets Regression for Object Detection
https://github.com/Scalsol/mega.pytorch
공식 코드Memory Enhanced Global-Local Aggregation for Video Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.