Papers with Code 아카이브

2D Object Detection

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하위 태스크

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평가표

20

보존된 평가 기록

57

코드

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

https://github.com/tum-traffic-dataset/coopdet3d

공식 코드

TUMTraf V2X Cooperative Perception Dataset

https://github.com/tum-traffic-dataset/tum-traffic-dataset-dev-kit

공식 코드

TUMTraf V2X Cooperative Perception Dataset

https://github.com/tumftm/caliv

공식 코드

CaLiV: LiDAR-to-Vehicle Calibration of Arbitrary Sensor Setups via Object Reconstruction

https://github.com/tumftm/dpft

공식 코드

DPFT: Dual Perspective Fusion Transformer for Camera-Radar-based Object Detection

https://github.com/tumftm/radargnn

공식 코드

RadarGNN: Transformation Invariant Graph Neural Network for Radar-based Perception

https://github.com/tumftm/sim2realdistributionaligneddataset

공식 코드

Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-Level

https://github.com/tunantu/dynamic-layer-attention

공식 코드

Strengthening Layer Interaction via Dynamic Layer Attention

https://github.com/turoad/scaloss

공식 코드

SCALoss: Side and Corner Aligned Loss for Bounding Box Regression

https://github.com/tusen-ai/mv2d

공식 코드

Object as Query: Lifting any 2D Object Detector to 3D Detection

https://github.com/tusen-ai/sst

공식 코드

Super Sparse 3D Object Detection

https://github.com/tusimple/centerformer

공식 코드

CenterFormer: Center-based Transformer for 3D Object Detection

https://github.com/tusimple/simpledet

공식 코드

SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition

https://github.com/tusimple/sst

공식 코드

Embracing Single Stride 3D Object Detector with Sparse Transformer

https://github.com/tustailab/hmpnet

공식 코드

HMPNet: A Feature Aggregation Architecture for Maritime Object Detection from a Shipborne Perspective

https://github.com/twangnh/Distilling-Object-Detectors

공식 코드

Distilling Object Detectors with Fine-grained Feature Imitation

https://github.com/twangnh/SimCal

공식 코드

The Devil is in Classification: A Simple Framework for Long-tail Object Detection and Instance Segmentation

https://github.com/twangnh/pnp-detr

공식 코드

PnP-DETR: Towards Efficient Visual Analysis with Transformers

https://github.com/tydpan/NorCal

공식 코드

On Model Calibration for Long-Tailed Object Detection and Instance Segmentation

https://github.com/tydpan/gpc

공식 코드

Pre-Training LiDAR-Based 3D Object Detectors Through Colorization

https://github.com/tyomj/product_detection

공식 코드

Working with scale: 2nd place solution to Product Detection in Densely Packed Scenes [Technical Report]

https://github.com/tztztztztz/eql.detectron2

공식 코드

Equalization Loss for Long-Tailed Object Recognition

https://github.com/tztztztztz/eqlv2

공식 코드

Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection

https://github.com/uark-aicv/meganet

공식 코드

MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation

https://github.com/ubamba98/EAD2020

공식 코드

Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection

https://github.com/uber-research/permute-quantize-finetune

공식 코드

Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks

https://github.com/uber/sbnet

공식 코드

SBNet: Sparse Blocks Network for Fast Inference

https://github.com/ucas-gyx/youtube-gdd

공식 코드

YouTube-GDD: A challenging gun detection dataset with rich contextual information

https://github.com/ucas-vg/TinyBenchmark

공식 코드

Scale Match for Tiny Person Detection

https://github.com/ucas-vg/p2bnet

공식 코드

Point-to-Box Network for Accurate Object Detection via Single Point Supervision

https://github.com/ucas-vg/pointtinybenchmark

공식 코드

Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes

https://github.com/ucbdrive/few-shot-object-detection

공식 코드

Frustratingly Simple Few-Shot Object Detection

https://github.com/ucla-mobility/v2v4real

공식 코드

V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception

https://github.com/ucr-robotics/citrus-farm-dataset

공식 코드

Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms

https://github.com/uddd821/hv-bev

공식 코드

HV-BEV: Decoupling Horizontal and Vertical Feature Sampling for Multi-View 3D Object Detection

https://github.com/uestc-nnlab/tridos

공식 코드

Triple-domain Feature Learning with Frequency-aware Memory Enhancement for Moving Infrared Small Target Detection

https://github.com/uestc-nnlab/wecol

공식 코드

Weakly-supervised Contrastive Learning with Quantity Prompts for Moving Infrared Small Target Detection

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