Papers with Code 아카이브

2D Object Detection

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전체 기법전체 데이터셋

하위 태스크

15

평가표

20

보존된 평가 기록

57

코드

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

https://github.com/visionxlab/whollywood

공식 코드

Wholly-WOOD: Wholly Leveraging Diversified-quality Labels for Weakly-supervised Oriented Object Detection

https://github.com/visionxlab/whollywood-jittor

공식 코드

Wholly-WOOD: Wholly Leveraging Diversified-quality Labels for Weakly-supervised Oriented Object Detection

https://github.com/visresearch/MultipleObjectStitching

공식 코드

Multiple Object Stitching for Unsupervised Representation Learning

https://github.com/visresearch/aps

공식 코드

Asymmetric Patch Sampling for Contrastive Learning

https://github.com/visresearch/mgc

공식 코드

Multi-Grained Contrast for Data-Efficient Unsupervised Representation Learning

https://github.com/visresearch/patchmix

공식 코드

Inter-Instance Similarity Modeling for Contrastive Learning

https://github.com/visual-conception-group/localized-perception-constrained-vision-systems

공식 코드

Resource Efficient Perception for Vision Systems

https://github.com/visual-words/visual-words

공식 코드

Understanding Visual Concepts Across Models

https://github.com/visualaikhu/monowad

공식 코드

MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object Detection

https://github.com/viswas1/TinyML

공식 코드

Real Time Object Detection System with YOLO and CNN Models: A Review

https://github.com/visym/keynet

공식 코드

Key-Nets: Optical Transformation Convolutional Networks for Privacy Preserving Vision Sensors

https://github.com/vita-epfl/butterflydetector

공식 코드

Perceiving Traffic from Aerial Images

https://github.com/vita-epfl/monoloco

공식 코드

MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation

https://github.com/vita-group/slak

공식 코드

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

https://github.com/vitae-transformer/bevsimdet

공식 코드

SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection

https://github.com/vitae-transformer/mtp

공식 코드

MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining

https://github.com/vitae-transformer/qformer

공식 코드

Vision Transformer with Quadrangle Attention

https://github.com/vitae-transformer/remote-sensing-rvsa

공식 코드

Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model

https://github.com/vitae-transformer/rsp

공식 코드

An Empirical Study of Remote Sensing Pretraining

https://github.com/vitae-transformer/samrs

공식 코드

SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model

https://github.com/vitae-transformer/simdistill

공식 코드

SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection

https://github.com/vitae-transformer/vitae-transformer-remote-sensing

공식 코드

An Empirical Study of Remote Sensing Pretraining

https://github.com/vitae-transformer/vitae-vsa

공식 코드

VSA: Learning Varied-Size Window Attention in Vision Transformers

https://github.com/vkakerbeck/FastConceptMapping

공식 코드

Fast Concept Mapping: The Emergence of Human Abilities in Artificial Neural Networks when Learning Embodied and Self-Supervised

https://github.com/vkalogeiton/yto-dataset

공식 코드

Analysing domain shift factors between videos and images for object detection

https://github.com/vladimirescu/robustdehazing

공식 코드

Fine-Tuning Adversarially-Robust Transformers for Single-Image Dehazing

https://github.com/vlbthambawita/divergent-nets

공식 코드

DivergentNets: Medical Image Segmentation by Network Ensemble

https://github.com/vlfom/rncdl

공식 코드

Learning to Discover and Detect Objects

https://github.com/vniclas/lidar_beam_selection

공식 코드

End-To-End Optimization of LiDAR Beam Configuration for 3D Object Detection and Localization

https://github.com/voyazici/visual-transformers-classification

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Visual Transformers with Primal Object Queries for Multi-Label Image Classification

https://github.com/vs-cv/sf-yolo

공식 코드

Source-Free Domain Adaptation for YOLO Object Detection

https://github.com/walzimmer/3d-bat

공식 코드

TUMTraf V2X Cooperative Perception Dataset

https://github.com/wandahangfy/yolov11-rgbt

공식 코드

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework

https://github.com/wang-chen/KCC

공식 코드

Kernel Cross-Correlator

https://github.com/wangbo-zhao/WSVSOD

공식 코드

Weakly Supervised Video Salient Object Detection

https://github.com/wangchen1801/fpd

공식 코드

Fine-Grained Prototypes Distillation for Few-Shot Object Detection

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