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/csuhan/vfa

공식 코드

Few-Shot Object Detection via Variational Feature Aggregation

https://github.com/csuvis/BarchartReverseEngineering

공식 코드

Reverse-engineering Bar Charts Using Neural Networks

https://github.com/csysi/fsel

공식 코드

Frequency-Spatial Entanglement Learning for Camouflaged Object Detection

https://github.com/csysi/glconet

공식 코드

GLCONet: Learning Multi-source Perception Representation for Camouflaged Object Detection

https://github.com/csysi/udcnet

공식 코드

United Domain Cognition Network for Salient Object Detection in Optical Remote Sensing Images

https://github.com/cszzshi/SimD

공식 코드

Similarity Distance-Based Label Assignment for Tiny Object Detection

https://github.com/ctu-vras/pcl-augmentation

공식 코드

Real3D-Aug: Point Cloud Augmentation by Placing Real Objects with Occlusion Handling for 3D Detection and Segmentation

https://github.com/ctu-vras/t-concord3d

공식 코드

Teachers in concordance for pseudo-labeling of 3D sequential data

https://github.com/ctuning/cbench

공식 코드

The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps

https://github.com/cuibaby/dpk

공식 코드

Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge Distillation

https://github.com/cuiziteng/eccv_aeris

공식 코드

Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection

https://github.com/cuiziteng/iccv_maet

공식 코드

Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection

https://github.com/cuiziteng/illumination-adaptive-transformer

공식 코드

You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction

https://github.com/cuiziteng/maet

공식 코드

Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection

https://github.com/cuogeihong/ceasc

공식 코드

Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images

https://github.com/cuong-pv/FAM-KD

공식 코드

Frequency Attention for Knowledge Distillation

https://github.com/cuppp1998/360_object_tracking

공식 코드

Multiple Object Detection and Tracking in Panoramic Videos for Cycling Safety Analysis

https://github.com/custommetrics-sst/sst_customevaluationmetrics

공식 코드

SST-EM: Advanced Metrics for Evaluating Semantic, Spatial and Temporal Aspects in Video Editing

https://github.com/cv-core/MIT-Driverless-CV-TrainingInfra

공식 코드

Accurate, Low-Latency Visual Perception for Autonomous Racing:Challenges, Mechanisms, and Practical Solutions

https://github.com/cv-zhangxin/akconv

공식 코드

LDConv: Linear deformable convolution for improving convolutional neural networks

https://github.com/cv-zhangxin/ldconv

공식 코드

LDConv: Linear deformable convolution for improving convolutional neural networks

https://github.com/cv516buaa/ov-vg

공식 코드

OV-VG: A Benchmark for Open-Vocabulary Visual Grounding

https://github.com/cviaai/dasha

공식 코드

DASHA: Decentralized Autofocusing System with Hierarchical Agents

https://github.com/cvignac/top-n

공식 코드

Top-N: Equivariant set and graph generation without exchangeability

https://github.com/cvlab-epfl/mvflow

공식 코드

Multi-view Tracking Using Weakly Supervised Human Motion Prediction

https://github.com/cvlab-stonybrook/Weighting-Pseudo-Labels

공식 코드

Weighting Pseudo-Labels via High-Activation Feature Index Similarity and Object Detection for Semi-Supervised Segmentation

https://github.com/cvlab-yonsei/HVPR

공식 코드

HVPR: Hybrid Voxel-Point Representation for Single-stage 3D Object Detection

https://github.com/cvmi-lab/codet

공식 코드

CoDet: Co-Occurrence Guided Region-Word Alignment for Open-Vocabulary Object Detection

https://github.com/cvmi-lab/fs3d

공식 코드

Prototypical VoteNet for Few-Shot 3D Point Cloud Object Detection

https://github.com/cvmi-lab/sparsekd

공식 코드

Towards Efficient 3D Object Detection with Knowledge Distillation

https://github.com/cvmi-lab/syncood

공식 코드

Can OOD Object Detectors Learn from Foundation Models?

https://github.com/cxliu0/oa-mil

공식 코드

Robust Object Detection With Inaccurate Bounding Boxes

https://github.com/cxt98/ACF_perception

공식 코드

Manipulation-Oriented Object Perception in Clutter through Affordance Coordinate Frames

https://github.com/cxy1997/3D_adapt_auto_driving

공식 코드

Train in Germany, Test in The USA: Making 3D Object Detectors Generalize

https://github.com/cxy1997/DiffuBox

공식 코드

DiffuBox: Refining 3D Object Detection with Point Diffusion

https://github.com/cybercore-co-ltd/CoLAD

공식 코드

Improving Object Detection by Label Assignment Distillation

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