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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/julimueller/disparity-sliding-window
공식 코드Disparity Sliding Window: Object Proposals From Disparity Images
https://github.com/julimueller/tl_ssd
공식 코드https://github.com/juliozhao97/efftrans_fsdet
공식 코드Exploring Effective Knowledge Transfer for Few-shot Object Detection
https://github.com/junayed/sonar-scan-dataset-with-ping-360
공식 코드https://github.com/junchen14/LoMaR
공식 코드Efficient Self-supervised Vision Pretraining with Local Masked Reconstruction
https://github.com/junfu1995/sgh
공식 코드Scale Guided Hypernetwork for Blind Super-Resolution Image Quality Assessment
https://github.com/junhyukk/MAMNet-Tensorflow
공식 코드MAMNet: Multi-path Adaptive Modulation Network for Image Super-Resolution
https://github.com/junhyung-SPALab/D-Align
공식 코드https://github.com/junjie18/cmt
공식 코드Cross Modal Transformer: Towards Fast and Robust 3D Object Detection
https://github.com/junjun-jiang/Face-Hallucination-Benchmark
공식 코드https://github.com/junjun-jiang/Hyperspectral-Image-Super-Resolution-Benchmark
공식 코드Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery
https://github.com/junjun-jiang/SSPSR
공식 코드Learning Spatial-Spectral Prior for Super-Resolution of Hyperspectral Imagery
https://github.com/junsang7777/rzsr
공식 코드RZSR: Reference-based Zero-Shot Super-Resolution with Depth Guided Self-Exemplars
https://github.com/junzhang2016/NTU4DRadLM
공식 코드NTU4DRadLM: 4D Radar-centric Multi-Modal Dataset for Localization and Mapping
https://github.com/justimyhxu/Dense-RepPoints
공식 코드Dense RepPoints: Representing Visual Objects with Dense Point Sets
https://github.com/justincdavis/cv2ext/tree/main/src/cv2ext/research/shift
공식 코드Context-aware Multi-Model Object Detection for Diversely Heterogeneous Compute Systems
https://github.com/justinkay/aldi
공식 코드Align and Distill: Unifying and Improving Domain Adaptive Object Detection
https://github.com/justlovesmile/earl
공식 코드https://github.com/jw-chae/sjtu
공식 코드https://github.com/jwgdmkj/lmlt
공식 코드LMLT: Low-to-high Multi-Level Vision Transformer for Image Super-Resolution
https://github.com/jwhgdeu/tsbp
공식 코드https://github.com/jwliang007/ikd
공식 코드Exploring Inconsistent Knowledge Distillation for Object Detection with Data Augmentation
https://github.com/jwwangchn/NWD
공식 코드A Normalized Gaussian Wasserstein Distance for Tiny Object Detection
https://github.com/jxr326/swinmcnet
공식 코드Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection
https://github.com/jyLin8100/GenSAM
공식 코드https://github.com/jycha98/specextend
공식 코드SpecExtend: A Drop-in Enhancement for Speculative Decoding of Long Sequences
https://github.com/jyfenggogo/instructdet
공식 코드InstructDET: Diversifying Referring Object Detection with Generalized Instructions
https://github.com/jyqi/giraffedet
공식 코드https://github.com/k-h-ismail/convnext-dcls
공식 코드https://github.com/k-h-ismail/dilated-convolution-with-learnable-spacings-pytorch
공식 코드https://github.com/k-radlak/IDCNN
공식 코드Deep Learning based Switching Filter for Impulsive Noise Removal in Color Images
https://github.com/k2okoh/mad
공식 코드https://github.com/k4ntz/moc
공식 코드Boosting Object Representation Learning via Motion and Object Continuity
https://github.com/kahroba2000/biogan
공식 코드BioGAN: An unpaired GAN-based image to image translation model for microbiological images
https://github.com/kai-liu001/2dquant
공식 코드2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.