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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/weathon/vcos
공식 코드ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object Segmentation
https://github.com/weigertlab/tarrow
공식 코드Self-supervised dense representation learning for live-cell microscopy with time arrow prediction
https://github.com/weiguangzhao/PBNet
공식 코드Divide and Conquer: 3D Point Cloud Instance Segmentation With Point-Wise Binarization
https://github.com/weijiemax/lssinst
공식 코드LSSInst: Improving Geometric Modeling in LSS-Based BEV Perception with Instance Representation
https://github.com/weijun88/F3Net
공식 코드F3Net: Fusion, Feedback and Focus for Salient Object Detection
https://github.com/weijun88/LDF
공식 코드https://github.com/weiliu89/caffe
공식 코드https://github.com/weitaikang/segvg
공식 코드SegVG: Transferring Object Bounding Box to Segmentation for Visual Grounding
https://github.com/weiyangdaren/streamdsgn-pytorch
공식 코드Real-time Stereo-based 3D Object Detection for Streaming Perception
https://github.com/weiyithu/FGR
공식 코드FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection
https://github.com/weiyithu/lidar-distillation
공식 코드LiDAR Distillation: Bridging the Beam-Induced Domain Gap for 3D Object Detection
https://github.com/weiyithu/surroundocc
공식 코드SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving
https://github.com/weizequan/tashr
공식 코드https://github.com/weizhou-geek/SFSN
공식 코드Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalness
https://github.com/weizhou-geek/srif
공식 코드Quality Assessment of Image Super-Resolution: Balancing Deterministic and Statistical Fidelity
https://github.com/wencheng-zhu/ckd
공식 코드CKD: Contrastive Knowledge Distillation from A Sample-wise Perspective
https://github.com/wenchima/miti-detr
공식 코드Miti-DETR: Object Detection based on Transformers with Mitigatory Self-Attention Convergence
https://github.com/wenguanwang/SODsurvey
공식 코드Salient Object Detection in the Deep Learning Era: An In-Depth Survey
https://github.com/wenhaoli-xmu/seco
공식 코드Training Long-Context LLMs Efficiently via Chunk-wise Optimization
https://github.com/wenhuchen/Table-Fact-Checking
공식 코드TabFact: A Large-scale Dataset for Table-based Fact Verification
https://github.com/wenlongjiao/frenet
공식 코드Efficient RAW Image Deblurring with Adaptive Frequency Modulation
https://github.com/went-liang/unsniffer
공식 코드Unknown Sniffer for Object Detection: Don't Turn a Blind Eye to Unknown Objects
https://github.com/wenweixu/keras-yolo3
공식 코드Underwater Fish Detection using Deep Learning for Water Power Applications
https://github.com/wenwenyu/MASTER-pytorch
공식 코드https://github.com/wenwenyu/tcm
공식 코드https://github.com/wenyu1009/rtsrn
공식 코드Pixel Adapter: A Graph-Based Post-Processing Approach for Scene Text Image Super-Resolution
https://github.com/wenyyu/Image-Adaptive-YOLO
공식 코드Image-Adaptive YOLO for Object Detection in Adverse Weather Conditions
https://github.com/wesleyhsieh0806/ss-prl
공식 코드Self-Supervised Pyramid Representation Learning for Multi-Label Visual Analysis and Beyond
https://github.com/westlake-ai/sema
공식 코드https://github.com/wgcban/DIP-HyperKite
공식 코드Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction
https://github.com/whai362/PVT
공식 코드Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
https://github.com/whileherham/calibratedteacher
공식 코드https://github.com/whxuuuu/vision-communication-dataset
공식 코드Computer Vision Aided mmWave Beam Alignment in V2X Communications
https://github.com/wiktormucha/SHARP
공식 코드https://github.com/wimh966/QDrop
공식 코드QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.