https://github.com/HKUST-Aerial-Robotics/Stereo-RCNN
공식 코드Stereo R-CNN based 3D Object Detection for Autonomous Driving
Papers with Code 아카이브
2D Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/HLTCHKUST/CAiRE-COVID
공식 코드https://github.com/HLTSingapore/Emotional-Speech-Data
공식 코드Seen and Unseen emotional style transfer for voice conversion with a new emotional speech dataset
https://github.com/HPL123/RRFS
공식 코드Robust Region Feature Synthesizer for Zero-Shot Object Detection
https://github.com/HSE-asavchenko/mobile-visual-preferences
공식 코드https://github.com/HVision-NKU/Strip-R-CNN
공식 코드Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection
https://github.com/HWQuantum/Simulating-single-photon-detector-array-sensors-for-depth-imaging
공식 코드Simulating single-photon detector array sensors for depth imaging
https://github.com/HYjhkoh/TM_VOD
공식 코드Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection
https://github.com/HZAI-ZJNU/SCSA
공식 코드SCSA: Exploring the Synergistic Effects Between Spatial and Channel Attention
https://github.com/HadiAskari/Relevance-Paraphrasing
공식 코드Assessing LLMs for Zero-shot Abstractive Summarization Through the Lens of Relevance Paraphrasing
https://github.com/HakkiMotorcu/HM-Net_WAMI
공식 코드HM-Net: A Regression Network for Object Center Detection and Tracking on Wide Area Motion Imagery
https://github.com/HanjiangHu/Multi-LiDAR-Placement-for-3D-Detection
공식 코드Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving
https://github.com/HaoGood/MOD
공식 코드Toward Minimal Misalignment at Minimal Cost in One-Stage and Anchor-Free Object Detection
https://github.com/HaochengWan/PVT
공식 코드https://github.com/HaojunYu1998/UltraDet
공식 코드https://github.com/HarmoniaLeo/FRLW-EvD
공식 코드Motion Robust High-Speed Light-Weighted Object Detection With Event Camera
https://github.com/HarrialX/GraphBackdoor
공식 코드https://github.com/HaydenCaffrey/SIG-VC
공식 코드https://github.com/HeathArhturLouis/Rethinking-Molecular-Design-Integrating-Latent-Variable-and-Autoregressive-Models-for-Enhanced-Goal
공식 코드https://github.com/Heliot7/viewpoint-cnn-syn
공식 코드Joint Viewpoint and Keypoint Estimation with Real and Synthetic Data
https://github.com/HelloWorldLTY/ARIEL
공식 코드Towards Artificial Intelligence Research Assistant for Expert-Involved Learning
https://github.com/HengerLi/RLBackdoorFL
공식 코드https://github.com/HengyiWang/MorpheuS
공식 코드MorpheuS: Neural Dynamic 360° Surface Reconstruction from Monocular RGB-D Video
https://github.com/HikariTJU/LD
공식 코드https://github.com/Hiyuur/SR-TOD
공식 코드https://github.com/Holmes-Alan/ST-VAE
공식 코드https://github.com/Holmes-Alan/TxST
공식 코드Name Your Style: An Arbitrary Artist-aware Image Style Transfer
https://github.com/HolmesShuan/Compact-Global-Descriptor
공식 코드https://github.com/HolmesShuan/Zero-shot-Style-Transfer-via-Attention-Rearrangement
공식 코드https://github.com/Holmeswww/PPOGAN
공식 코드Improving GAN Training with Probability Ratio Clipping and Sample Reweighting
https://github.com/HongguangZhang/DMPHN-cvpr19-master
공식 코드Event-guided Multi-patch Network with Self-supervision for Non-uniform Motion Deblurring
https://github.com/Howal/Cross-iterationBatchNorm
공식 코드https://github.com/Howal/DNL-Object-Detection
공식 코드https://github.com/Hryniewska/checklist
공식 코드https://github.com/HsinYingLee/OPN
공식 코드https://github.com/HuanBor/AttenST
공식 코드AttenST: A Training-Free Attention-Driven Style Transfer Framework with Pre-Trained Diffusion Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.