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/chaoqichen/HTCN

공식 코드

Harmonizing Transferability and Discriminability for Adapting Object Detectors

https://github.com/chaoxiao12/moving-object-detection-in-satellite-videos-hieum

공식 코드

Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos

https://github.com/charlesq34/frustum-pointnets

공식 코드

Frustum PointNets for 3D Object Detection from RGB-D Data

https://github.com/charliebudd/torch-content-area

공식 코드

Rapid and robust endoscopic content area estimation: A lean GPU-based pipeline and curated benchmark dataset

https://github.com/chasel-tsui/mmdet-rfla

공식 코드

RFLA: Gaussian Receptive Field based Label Assignment for Tiny Object Detection

https://github.com/chasel-tsui/mmrotate-dcfl

공식 코드

Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detection

https://github.com/chaytonmin/occ-bev

공식 코드

UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous Driving

https://github.com/chaytonmin/occupancy-mae

공식 코드

Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders

https://github.com/chaytonmin/uniscene

공식 코드

UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous Driving

https://github.com/chaytonmin/voxel-mae

공식 코드

Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders

https://github.com/cheerss/CrossFormer

공식 코드

CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention

https://github.com/cheind/pytorch-blender

공식 코드

BlendTorch: A Real-Time, Adaptive Domain Randomization Library

https://github.com/cheliosoops/bitq

공식 코드

BitQ: Tailoring Block Floating Point Precision for Improved DNN Efficiency on Resource-Constrained Devices

https://github.com/cheliu-computation/g2d-neurips24

공식 코드

G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training

https://github.com/cheliu-computation/m-flag-miccai2023

공식 코드

M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization

https://github.com/cheliu-computation/medsyn-replearn

공식 코드

Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images

https://github.com/chen-du/De-fencing

공식 코드

Accurate and efficient video de-fencing using convolutional neural networks and temporal information

https://github.com/chen-xin-94/dart

공식 코드

DART: An Automated End-to-End Object Detection Pipeline with Data Diversification, Open-Vocabulary Bounding Box Annotation, Pseudo-Label Review, and Model Training

https://github.com/chen-xin-94/ocdet

공식 코드

OCDet: Object Center Detection via Bounding Box-Aware Heatmap Prediction on Edge Devices with NPUs

https://github.com/chen37058/physical-attacks-in-embodied-nav

공식 코드

Towards Physically Realizable Adversarial Attacks in Embodied Vision Navigation

https://github.com/chen37058/physical-attacks-in-embodied-navigation

공식 코드

Towards Physically Realizable Adversarial Attacks in Embodied Vision Navigation

https://github.com/chenastron/mtunet

공식 코드

A Multi-task Framework for Infrared Small Target Detection and Segmentation

https://github.com/chenbinghui1/dsl

공식 코드

Dense Learning based Semi-Supervised Object Detection

https://github.com/cheng052/BRNet

공식 코드

Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds

https://github.com/chengshiest/plain-det

공식 코드

Plain-Det: A Plain Multi-Dataset Object Detector

https://github.com/chengshiest/zip-your-clip

공식 코드

The devil is in the object boundary: towards annotation-free instance segmentation using Foundation Models

https://github.com/chengtan9907/OpenSTL

공식 코드

MogaNet: Multi-order Gated Aggregation Network

https://github.com/chengtao-lv/ptq4sam

공식 코드

PTQ4SAM: Post-Training Quantization for Segment Anything

https://github.com/chengxihan/cgnet-cd

공식 코드

Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery

https://github.com/chengyangfu/retinamask

공식 코드

RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

https://github.com/chengzhag/Implicit3DUnderstanding

공식 코드

Holistic 3D Scene Understanding from a Single Image with Implicit Representation

https://github.com/chenhaomingbob/csc

공식 코드

Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception

https://github.com/chenhongyiyang/gpvit

공식 코드

GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation

https://github.com/chenhongyiyang/pgd

공식 코드

Prediction-Guided Distillation for Dense Object Detection

https://github.com/chenhongyiyang/plainmamba

공식 코드

PlainMamba: Improving Non-Hierarchical Mamba in Visual Recognition

https://github.com/chenhongyiyang/ppal

공식 코드

Plug and Play Active Learning for Object Detection

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