Papers with Code 아카이브

Object Detection

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전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

https://github.com/yinjunbo/proficientteachers

공식 코드

Semi-supervised 3D Object Detection with Proficient Teachers

https://github.com/yinjunbo/proposalcontrast

공식 코드

ProposalContrast: Unsupervised Pre-training for LiDAR-based 3D Object Detection

https://github.com/yinjunbo/ssda3d

공식 코드

SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud

https://github.com/yinmh17/DNL-Semantic-Segmentation

공식 코드

Disentangled Non-Local Neural Networks

https://github.com/yinyf0804/wsod-cbl

공식 코드

Cyclic-Bootstrap Labeling for Weakly Supervised Object Detection

https://github.com/yinyunie/RfDNet

공식 코드

RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction

https://github.com/yinyunie/Total3DUnderstanding

공식 코드

Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image

https://github.com/yiqunchen1999/date

공식 코드

DATE: Dual Assignment for End-to-End Fully Convolutional Object Detection

https://github.com/yixuan-2002/sea

공식 코드

Rethinking the Evaluation of Visible and Infrared Image Fusion

https://github.com/yixuan730/DetToolChain

공식 코드

DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM

https://github.com/yizhou-wang/RODNet

공식 코드

RODNet: Radar Object Detection Using Cross-Modal Supervision

https://github.com/yjybuaa/plantcamo

공식 코드

PlantCamo: Plant Camouflage Detection

https://github.com/yjzhao19981027/datformer

공식 코드

Distortion-aware Transformer in 360° Salient Object Detection

https://github.com/ykotseruba/snap

공식 코드

SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision Tasks

https://github.com/ylwhxht/l4dr

공식 코드

L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection

https://github.com/ylwhxht/v2x-r

공식 코드

V2X-R: Cooperative LiDAR-4D Radar Fusion for 3D Object Detection with Denoising Diffusion

https://github.com/yn-yang/sfnet

공식 코드

Enhancing Traffic Object Detection in Variable Illumination with RGB-Event Fusion

https://github.com/yoavarad/mfad

공식 코드

Beyond the Benchmark: Detecting Diverse Anomalies in Videos

https://github.com/yoctta/xpaste

공식 코드

X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion

https://github.com/yoloonme/ema-attention-module

공식 코드

Efficient Multi-Scale Attention Module with Cross-Spatial Learning

https://github.com/yonghaohe/dsla

공식 코드

DSLA: Dynamic smooth label assignment for efficient anchor-free object detection

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/youngfly/Dynamic-Adjustment-Fusion

공식 코드

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

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

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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

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