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

https://github.com/XiongweiWu/Awesome-Object-Detection

공식 코드

Recent Advances in Deep Learning for Object Detection

https://github.com/Xuan-World/Mamba-YOLO-World

공식 코드

Mamba-YOLO-World: Marrying YOLO-World with Mamba for Open-Vocabulary Detection

https://github.com/XueHaoWang-Beijing/DQSF

공식 코드

Knowing Depth Quality In Advance: A Depth Quality Assessment Method For RGB-D Salient Object Detection

https://github.com/XueHaoWang-Beijing/DRLF

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Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection

https://github.com/XuechenZhang123/LCSC

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LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-Resolution

https://github.com/XunshanMan/Object-oriented-SLAM

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Object-oriented SLAM using Quadrics and Symmetry Properties for Indoor Environments

https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy

공식 코드

Diffusion Models: A Comprehensive Survey of Methods and Applications

https://github.com/YanghaoZYH/HNM-PGD

공식 코드

Fooling Object Detectors: Adversarial Attacks by Half-Neighbor Masks

https://github.com/YeLyuUT/VOSDetectron

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Plug & Play Convolutional Regression Tracker for Video Object Detection

https://github.com/YeRen123455/Infrared-Small-Target-Detection

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Dense Nested Attention Network for Infrared Small Target Detection

https://github.com/YeolJ00/faster-rcnn-pytorch

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Graudally Applying Weakly Supervised and Active Learning for Mass Detection in Breast Ultrasound Images

https://github.com/YeongjinOh/Sushi-Dish

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Sushi Dish - Object detection and classification from real images

https://github.com/YingqianWang/LF-InterNet

공식 코드

Spatial-Angular Interaction for Light Field Image Super-Resolution

https://github.com/YingqianWang/NUDT-Dataset

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Light Field Image Super-Resolution Using Deformable Convolution

https://github.com/YingqianWang/iPASSR

공식 코드

Symmetric Parallax Attention for Stereo Image Super-Resolution

https://github.com/YinminZhang/MonoGeo

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Learning Geometry-Guided Depth via Projective Modeling for Monocular 3D Object Detection

https://github.com/Yonsei-STL/pix2next

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Pix2Next: Leveraging Vision Foundation Models for RGB to NIR Image Translation

https://github.com/YoushaaMurhij/FMFNet

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Real-time 3D Object Detection using Feature Map Flow

https://github.com/YuanfeiHuang/DeFiAN

공식 코드

Interpretable Detail-Fidelity Attention Network for Single Image Super-Resolution

https://github.com/YuanfeiHuang/IKM

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Image-specific Convolutional Kernel Modulation for Single Image Super-resolution

https://github.com/YueLiao/CDN

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Mining the Benefits of Two-stage and One-stage HOI Detection

https://github.com/YueLiao/PPDM

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PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection

https://github.com/YuemingJin/MTRCNet-CL

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Multi-Task Recurrent Convolutional Network with Correlation Loss for Surgical Video Analysis

https://github.com/Yuheng-SWJTU/pyramid-discrete-diffusion

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Pyramid Diffusion for Fine 3D Large Scene Generation

https://github.com/Yuki-11/NTIRE2023_ShadowRemoval_IIM_TTI

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NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI

https://github.com/Yuliang-Liu/TIoU-metric

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Tightness-aware Evaluation Protocol for Scene Text Detection

https://github.com/Yuri3-xr/NMS-Bench

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Accelerating Non-Maximum Suppression: A Graph Theory Perspective

https://github.com/YuvalBahat/Explorable-Super-Resolution/tree/gh-pages/codes

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Explorable Super Resolution

https://github.com/YuvalNirkin/hyperseg

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HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation

https://github.com/YuzheZhang-1999/DiffTSR

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Diffusion-based Blind Text Image Super-Resolution

https://github.com/Yzichen/FlashOCC

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FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugin

https://github.com/ZFTurbo/Weighted-Boxes-Fusion

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Weighted boxes fusion: Ensembling boxes from different object detection models

https://github.com/ZHANGHeng19931123/CFR

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Multispectral Fusion for Object Detection with Cyclic Fuse-and-Refine Blocks

https://github.com/ZHANGHeng19931123/MutualGuide

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Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection

https://github.com/ZJULearning/ttfnet

공식 코드

Training-Time-Friendly Network for Real-Time Object Detection

https://github.com/ZLeopard/PEDCC-Loss

공식 코드

A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids

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