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/tencentyouturesearch/visualrecognition-nommer

공식 코드

NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition

https://github.com/tennine2077/pdfnet

공식 코드

Patch-Depth Fusion: Dichotomous Image Segmentation via Fine-Grained Patch Strategy and Depth Integrity-Prior

https://github.com/tensorflow/lingvo

공식 코드

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection

https://github.com/tensorflow/models

공식 코드

MnasFPN: Learning Latency-aware Pyramid Architecture for Object Detection on Mobile Devices

https://github.com/tensorflow/models/tree/master/official/vision/beta/modeling/backbones

공식 코드

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

https://github.com/tensorflow/models/tree/master/research/lstm_object_detection

공식 코드

Looking Fast and Slow: Memory-Guided Mobile Video Object Detection

https://github.com/tensorflow/tensorflow

공식 코드

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals

https://github.com/tensorflow/tensorflow/blob/v2.4.1/tensorflow/python/keras/applications/mobilenet.py

공식 코드

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/tensorflow/tpu

공식 코드

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/tensorflow/tpu/tree/master/models/official/detection/projects/copy_paste

공식 코드

Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation

https://github.com/tensorflow/tpu/tree/master/models/official/detection/projects/vild

공식 코드

Open-vocabulary Object Detection via Vision and Language Knowledge Distillation

https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet

공식 코드

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/terry9a/dsrc

공식 코드

DSRC: Learning Density-insensitive and Semantic-aware Collaborative Representation against Corruptions

https://github.com/teryzh/roadside-lidar-vehicle-detection-and-tracking-background-subtraction

공식 코드

Roadside Lidar Vehicle Detection and Tracking Using Range And Intensity Background Subtraction

https://github.com/texasinstruments/edgeai-yolov5

공식 코드

YOLO-Pose: Enhancing YOLO for Multi Person Pose Estimation Using Object Keypoint Similarity Loss

https://github.com/texasinstruments/edgeai-yolox

공식 코드

YOLO-Pose: Enhancing YOLO for Multi Person Pose Estimation Using Object Keypoint Similarity Loss

https://github.com/tfwu/FaceDetection-ConvNet-3D

공식 코드

Face Detection with End-to-End Integration of a ConvNet and a 3D Model

https://github.com/tgisaturday/L-Verse

공식 코드

L-Verse: Bidirectional Generation Between Image and Text

https://github.com/tgxs002/cora

공식 코드

CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching

https://github.com/thangvubk/Cascade-RPN

공식 코드

Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution

https://github.com/thangvubk/softgroup

공식 코드

SoftGroup for 3D Instance Segmentation on Point Clouds

https://github.com/theimad/cricket-image-segmentation

공식 코드

Deep-Learning-Based Computer Vision Approach For The Segmentation Of Ball Deliveries And Tracking In Cricket

https://github.com/thensib/repvgg-gelan

공식 코드

RepVGG-GELAN: Enhanced GELAN with VGG-STYLE ConvNets for Brain Tumour Detection

https://github.com/theodpzz/uav-localization

공식 코드

Leveraging edge detection and neural networks for better UAV localization

https://github.com/therebellll/NegIoU-PosIoU-Miou

공식 코드

Optimized Loss Functions for Object detection: A Case Study on Nighttime Vehicle Detection

https://github.com/therock90421/da-ada

공식 코드

DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection

https://github.com/thesstefan/pixlens

공식 코드

PixLens: A Novel Framework for Disentangled Evaluation in Diffusion-Based Image Editing with Object Detection + SAM

https://github.com/thinklab-sjtu/twns

공식 코드

Ternary Weight Networks

https://github.com/thograce/C2FNet

공식 코드

Context-aware Cross-level Fusion Network for Camouflaged Object Detection

https://github.com/thograce/bgnet

공식 코드

Boundary-Guided Camouflaged Object Detection

https://github.com/thomasjo/nemo-redux

공식 코드

Instance Segmentation of Microscopic Foraminifera

https://github.com/thsant/add256-fastercnn

공식 코드

A methodology for detection and localization of fruits in apples orchards from aerial images

https://github.com/thu-mig/yolo-uniow

공식 코드

YOLO-UniOW: Efficient Universal Open-World Object Detection

https://github.com/thu-ml/imagenet-a-plus

공식 코드

Rethinking Natural Adversarial Examples for Classification Models

https://github.com/thu-ml/oddefense

공식 코드

On the Importance of Backbone to the Adversarial Robustness of Object Detectors

https://github.com/thu17cyz/3DIoUMatch

공식 코드

3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection

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