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평가표

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보존된 평가 기록

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yongliuy/ditn

공식 코드

Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution

https://github.com/yongliuy/patchscaler

공식 코드

PatchScaler: An Efficient Patch-Independent Diffusion Model for Image Super-Resolution

https://github.com/yongsongh/aidsrgan-miccai2022

공식 코드

Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN

https://github.com/yongsongh/dasrgan

공식 코드

Texture and Noise Dual Adaptation for Infrared Image Super-Resolution

https://github.com/yongsongh/infrared_image_sr_survey

공식 코드

Infrared Image Super-Resolution: Systematic Review, and Future Trends

https://github.com/yongsongh/irsrmamba

공식 코드

IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model

https://github.com/yongxinw/GSDT

공식 코드

Joint Object Detection and Multi-Object Tracking with Graph Neural Networks

https://github.com/yoojy31/mdod

공식 코드

Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image

https://github.com/yoshitomo-matsubara/hnd-ghnd-object-detectors

공식 코드

Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks

https://github.com/yoshitomo-matsubara/ladon-multi-task-sc2

공식 코드

A Multi-task Supervised Compression Model for Split Computing

https://github.com/yoshitomo-matsubara/torchdistill

공식 코드

torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation

https://github.com/youcanbaby/mh-detr

공식 코드

MH-DETR: Video Moment and Highlight Detection with Cross-modal Transformer

https://github.com/youngfly/Dynamic-Adjustment-Fusion

공식 코드

Explore the LiDAR-Camera Dynamic Adjustment Fusion for 3D Object Detection

https://github.com/younghanstark/rhapsody

공식 코드

Rhapsody: A Dataset for Highlight Detection in Podcasts

https://github.com/youngsean/nids-net

공식 코드

Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation

https://github.com/youngskkim/CRN

공식 코드

CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perception

https://github.com/youngwanLEE/CenterMask

공식 코드

CenterMask : Real-Time Anchor-Free Instance Segmentation

https://github.com/youngwanLEE/MPViT

공식 코드

MPViT: Multi-Path Vision Transformer for Dense Prediction

https://github.com/youngwanLEE/rc-mae

공식 코드

Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders

https://github.com/yoursever/fakeparaegg

공식 코드

Copy-Move Detection in Optical Microscopy: A Segmentation Network and A Dataset

https://github.com/youshaamurhij/rvcdet

공식 코드

Rethinking Voxelization and Classification for 3D Object Detection

https://github.com/youshyee/dcl-detection

공식 코드

Dynamic Curriculum Learning for Great Ape Detection in the Wild

https://github.com/yrahul3910/adaptive-lr-dnn

공식 코드

LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence

https://github.com/yrcong/RelTR

공식 코드

RelTR: Relation Transformer for Scene Graph Generation

https://github.com/ysj9909/DG-SoRA

공식 코드

SoRA: Singular Value Decomposed Low-Rank Adaptation for Domain Generalizable Representation Learning

https://github.com/ysj9909/SHViT

공식 코드

SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design

https://github.com/ysyscool/PSGLoss

공식 코드

Progressive Self-Guided Loss for Salient Object Detection

https://github.com/ytongbai/SemanticPartDetection

공식 코드

Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints from Limited Training Data

https://github.com/yuan-yutao/ecdp

공식 코드

Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolution

https://github.com/yuankaihuo/EasierPath

공식 코드

EasierPath: An Open-source Tool for Human-in-the-loop Deep Learning of Renal Pathology

https://github.com/yuanmaoxun/c2former

공식 코드

$\mathbf{C}^2$Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection

https://github.com/yuanmaoxun/calibrated-and-complementary-transformer-for-rgb-infrared-object-detection

공식 코드

$\mathbf{C}^2$Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection

https://github.com/yuantn/MI-AOD

공식 코드

Multiple instance active learning for object detection

https://github.com/yuanyunshuang/cosense3d

공식 코드

CoSense3D: an Agent-based Efficient Learning Framework for Collective Perception

https://github.com/yuanyunshuang/fpv_rcnn

공식 코드

Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous Driving

https://github.com/yuanyunshuang/gevbev

공식 코드

Generating Evidential BEV Maps in Continuous Driving Space

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.