https://github.com/lwpyh/ProMaC_code
공식 코드Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable Segmentation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lxj-drifter/uiou_files
공식 코드https://github.com/lxtGH/GALD-Net
공식 코드Global Aggregation then Local Distribution in Fully Convolutional Networks
https://github.com/lxtGH/SFSegNets
공식 코드https://github.com/lxycopper/plu
공식 코드Proposal-Level Unsupervised Domain Adaptation for Open World Unbiased Detector
https://github.com/lyanna4869/InfRS
공식 코드InfRS: Incremental Few-Shot Object Detection in Remote Sensing Images
https://github.com/lycexe/structsr
공식 코드StructSR: Refuse Spurious Details in Real-World Image Super-Resolution
https://github.com/lyclyc52/nerf_rpn
공식 코드https://github.com/lyessaadsaoud/adod
공식 코드ADOD: Adaptive Domain-Aware Object Detection with Residual Attention for Underwater Environments
https://github.com/lyhdet/ov-3det
공식 코드Open-Vocabulary Point-Cloud Object Detection without 3D Annotation
https://github.com/lyu-yx/acumen
공식 코드https://github.com/lyumengyao/blad
공식 코드https://github.com/lyuwenyu/RT-DETR
공식 코드https://github.com/lywang3081/MRDC
공식 코드https://github.com/lz118/Multi-interactive-Dual-decoder
공식 코드Multi-interactive Dual-decoder for RGB-thermal Salient Object Detection
https://github.com/lz118/Multi-interactive-Siamese-Decoder
공식 코드Multi-interactive Dual-decoder for RGB-thermal Salient Object Detection
https://github.com/lz118/RGBT-Salient-Object-Detection
공식 코드RGBT Salient Object Detection: A Large-scale Dataset and Benchmark
https://github.com/lzccccc/SMOKE
공식 코드SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation
https://github.com/lzh420202/fcosr
공식 코드FCOSR: A Simple Anchor-free Rotated Detector for Aerial Object Detection
https://github.com/lzx1413/CAFFE_SSD
공식 코드https://github.com/lzyhha/aodraw
공식 코드https://github.com/lzzcd001/MeshDiffusion
공식 코드https://github.com/lzzzzzm/ii-world
공식 코드$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting
https://github.com/m-g-a/3d-metrics
공식 코드Bounding Box Disparity: 3D Metrics for Object Detection With Full Degree of Freedom
https://github.com/m-g-a/care3d
공식 코드Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments
https://github.com/m-nauta/pipnet
공식 코드Interpreting and Correcting Medical Image Classification with PIP-Net
https://github.com/m4nh/ars
공식 코드https://github.com/ma-xu/fcvit
공식 코드A Close Look at Spatial Modeling: From Attention to Convolution
https://github.com/machengcheng2016/Subspace-Prompt-Learning
공식 코드Understanding and Mitigating Overfitting in Prompt Tuning for Vision-Language Models
https://github.com/machengcheng2016/crossteaching-ssod
공식 코드CrossRectify: Leveraging Disagreement for Semi-supervised Object Detection
https://github.com/maclong01/DeBiFormer
공식 코드DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention
https://github.com/madave94/gtiod
공식 코드https://github.com/maelic/sgg-benchmark
공식 코드REACT: Real-time Efficiency and Accuracy Compromise for Tradeoffs in Scene Graph Generation
https://github.com/magic-research/dataset_quantization
공식 코드https://github.com/magrinigabriele/nerdd
공식 코드Neuromorphic Drone Detection: an Event-RGB Multimodal Approach
https://github.com/mahdi65/roadDamageDetection2020
공식 코드An Efficient and Scalable Deep Learning Approach for Road Damage Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.