Papers with Code 아카이브

2D Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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/giddyyupp/coco-minitrain

공식 코드

HoughNet: Integrating near and long-range evidence for bottom-up object detection

https://github.com/gistairc/HS-SOD

공식 코드

Hyperspectral Image Dataset for Benchmarking on Salient Object Detection

https://github.com/git-disl/EVA

공식 코드

Parallel Detection for Efficient Video Analytics at the Edge

https://github.com/git-disl/TOG

공식 코드

TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems

https://github.com/git-disl/heterobust

공식 코드

Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness

https://github.com/git-disl/stdlens

공식 코드

STDLens: Model Hijacking-Resilient Federated Learning for Object Detection

https://github.com/gitmehrdad/sfsort

공식 코드

SFSORT: Scene Features-based Simple Online Real-Time Tracker

https://github.com/giuliomattolin/confmix

공식 코드

ConfMix: Unsupervised Domain Adaptation for Object Detection via Confidence-based Mixing

https://github.com/gjj45/dams-detr

공식 코드

DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion

https://github.com/gjj45/damsdet

공식 코드

DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion

https://github.com/gkioxari/RstarCNN

공식 코드

Contextual Action Recognition with R*CNN

https://github.com/gkw0010/gtav_head-dataset

공식 코드

Mask Focal Loss: A unifying framework for dense crowd counting with canonical object detection networks

https://github.com/gokulkarthik/deformable-detr

공식 코드

An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers

https://github.com/gokulkarthik/detr

공식 코드

An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers

https://github.com/gokyildirim/salmon_dataset

공식 코드

Evaluating Salient Object Detection in Natural Images with Multiple Objects having Multi-level Saliency

https://github.com/goodarzmehr/simbev

공식 코드

SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset

https://github.com/goodproj13/SG-Net

공식 코드

SG-Net: Spatial Granularity Network for One-Stage Video Instance Segmentation

https://github.com/goodproj13/tf-blender

공식 코드

TF-Blender: Temporal Feature Blender for Video Object Detection

https://github.com/google-research-datasets/Objectron

공식 코드

Objectron: A Large Scale Dataset of Object-Centric Videos in the Wild with Pose Annotations

https://github.com/google-research/augmix

공식 코드

AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty

https://github.com/google-research/big_vision

공식 코드

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

https://github.com/google-research/deeplab2

공식 코드

kMaX-DeepLab: k-means Mask Transformer

https://github.com/google-research/google-research

공식 코드

Stand-Alone Self-Attention in Vision Models

https://github.com/google-research/google-research/tree/master/fvlm

공식 코드

F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models

https://github.com/google-research/google-research/tree/master/fvlm/dito

공식 코드

Region-centric Image-Language Pretraining for Open-Vocabulary Detection

https://github.com/google-research/google-research/tree/master/fvlm/rovit

공식 코드

Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers

https://github.com/google-research/google-research/tree/master/muller

공식 코드

MULLER: Multilayer Laplacian Resizer for Vision

https://github.com/google-research/maxvit

공식 코드

MaxViT: Multi-Axis Vision Transformer

https://github.com/google-research/pix2seq

공식 코드

Pix2seq: A Language Modeling Framework for Object Detection

https://github.com/google-research/scenic/tree/main/scenic/projects/owl_vit

공식 코드

Simple Open-Vocabulary Object Detection with Vision Transformers

https://github.com/google-research/ssl_detection

공식 코드

A Simple Semi-Supervised Learning Framework for Object Detection

https://github.com/google-research/vision_transformer

공식 코드

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

https://github.com/google/automl

공식 코드

EfficientDet: Scalable and Efficient Object Detection

https://github.com/gorilla-lab-scut/vista

공식 코드

VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention

https://github.com/gpt4vision/OvSGTR

공식 코드

Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and Retention

https://github.com/gqding/SUDF

공식 코드

Salient object detection on hyperspectral images using features learned from unsupervised segmentation task

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