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/zhuoxiao-chen/mos

공식 코드

MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection

https://github.com/zhuoxiao-chen/redb-da-3ddet

공식 코드

Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling

https://github.com/zhuxing0/sa-radar

공식 코드

Simulate Any Radar: Attribute-Controllable Radar Simulation via Waveform Parameter Embedding

https://github.com/zhuzi24/sgg-toolkit

공식 코드

STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery

https://github.com/zichengduan/mvchm

공식 코드

Multiview Detection with Cardboard Human Modeling

https://github.com/zillur-av/wrong-way-vehicle-detection

공식 코드

A Real-Time Wrong-Way Vehicle Detection Based on YOLO and Centroid Tracking

https://github.com/zimoqingfeng/umop

공식 코드

Progressive Hard-case Mining across Pyramid Levels for Object Detection

https://github.com/ziongo6/fadet

공식 코드

FADet: A Multi-sensor 3D Object Detection Network based on Local Featured Attention

https://github.com/zip-group/litv2

공식 코드

Fast Vision Transformers with HiLo Attention

https://github.com/ziplab/litv2

공식 코드

Fast Vision Transformers with HiLo Attention

https://github.com/ziplab/qtool

공식 코드

AQD: Towards Accurate Fully-Quantized Object Detection

https://github.com/ziwei89/fbod

공식 코드

A Flying Bird Object Detection Method for Surveillance Video

https://github.com/ziweiwangthu/seernet

공식 코드

Learning Accurate Performance Predictors for Ultrafast Automated Model Compression

https://github.com/ziyueqingwan/localglobalattention

공식 코드

Local-Global Attention: An Adaptive Mechanism for Multi-Scale Feature Integration

https://github.com/ziyuey/uncertainty-aware-human-machine-collaboration-in-camouflaged-object-identification

공식 코드

Uncertainty Aware Human-machine Collaboration in Camouflaged Object Detection

https://github.com/ziyujia/SalientSleepNet

공식 코드

SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging

https://github.com/zjlab-ammi/ckim

공식 코드

Towards Commonsense Knowledge based Fuzzy Systems for Supporting Size-Related Fine-Grained Object Detection

https://github.com/zjlab-ammi/demix

공식 코드

Use the Detection Transformer as a Data Augmenter

https://github.com/zjsong/sacl

공식 코드

Enhancing Sound Source Localization via False Negative Elimination

https://github.com/zju3dv/disprcnn

공식 코드

Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation

https://github.com/zjulearning/srdet

공식 코드

Suppress-and-Refine Framework for End-to-End 3D Object Detection

https://github.com/zjw700/mus-cdb

공식 코드

MUS-CDB: Mixed Uncertainty Sampling with Class Distribution Balancing for Active Annotation in Aerial Object Detection

https://github.com/zjzwzw/ced-food

공식 코드

Boosting Few-Shot Open-Set Object Detection via Prompt Learning and Robust Decision Boundary

https://github.com/zk2172-columbia/boundless

공식 코드

Boundless: Generating Photorealistic Synthetic Data for Object Detection in Urban Streetscapes

https://github.com/zk2172-columbia/constellation-dataset

공식 코드

Constellation Dataset: Benchmarking High-Altitude Object Detection for an Urban Intersection

https://github.com/zkkli/psaq-vit

공식 코드

PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers

https://github.com/zkytony/genmos_object_search

공식 코드

A System for Generalized 3D Multi-Object Search

https://github.com/zl1994/IoU-Uniform-R-CNN

공식 코드

IoU-uniform R-CNN: Breaking Through the Limitations of RPN

https://github.com/zlichen/vectorformer

공식 코드

Learning High-resolution Vector Representation from Multi-Camera Images for 3D Object Detection

https://github.com/zllxot/core

공식 코드

CORE: Cooperative Reconstruction for Multi-Agent Perception

https://github.com/zongdai/autoshape

공식 코드

AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

https://github.com/zongwei97/popnet

공식 코드

Source-free Depth for Object Pop-out

https://github.com/zongzi13545329/simada

공식 코드

SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenes

https://github.com/zpdu/dai-net

공식 코드

Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation

https://github.com/zpywhu/pointobb-v3

공식 코드

PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection

https://github.com/zq-zang/descreg

공식 코드

Zero-Shot Aerial Object Detection with Visual Description Regularization

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