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/chreisinger/ViLGOD

공식 코드

Vision-Language Guidance for LiDAR-based Unsupervised 3D Object Detection

https://github.com/chrisjtan/RWS

공식 코드

A Self-supervised Learning System for Object Detection in Videos Using Random Walks on Graphs

https://github.com/chriswise07/imperceptible-patch-generator

공식 코드

Developing Imperceptible Adversarial Patches to Camouflage Military Assets From Computer Vision Enabled Technologies

https://github.com/chuanyangzheng/iformer

공식 코드

iFormer: Integrating ConvNet and Transformer for Mobile Application

https://github.com/chumingqian/Model_Compression_For_YOLOV3-V4

공식 코드

Group channel pruning and spatial attention distilling for object detection

https://github.com/chungyi347/interactive-multi-class-tiny-object-detection

공식 코드

Interactive Multi-Class Tiny-Object Detection

https://github.com/chunminghe/awesome-concealed-object-segmentation

공식 코드

A Survey of Camouflaged Object Detection and Beyond

https://github.com/chunminghe/camouflageator

공식 코드

Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects

https://github.com/chuxiuhong/dualteacher

공식 코드

DualTeacher: Bridging Coexistence of Unlabelled Classes for Semi-supervised Incremental Object Detection

https://github.com/chwilms/AttentionMask

공식 코드

AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects

https://github.com/chwilms/superpixelRefinement

공식 코드

Superpixel-based Refinement for Object Proposal Generation

https://github.com/cimagroup/experiments-surveygreenai

공식 코드

An In-Depth Analysis of Data Reduction Methods for Sustainable Deep Learning

https://github.com/cimagroup/experimentsod-surveygreenai

공식 코드

An In-Depth Analysis of Data Reduction Methods for Sustainable Deep Learning

https://github.com/cimagroup/surveygreenai

공식 코드

An In-Depth Analysis of Data Reduction Methods for Sustainable Deep Learning

https://github.com/cinderyl/lidattack

공식 코드

LiDAttack: Robust Black-box Attack on LiDAR-based Object Detection

https://github.com/cityu-aim-group/nlte

공식 코드

Towards Robust Adaptive Object Detection under Noisy Annotations

https://github.com/cityu-aim-group/sigma

공식 코드

SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection

https://github.com/cjw2021/QAHOI

공식 코드

QAHOI: Query-Based Anchors for Human-Object Interaction Detection

https://github.com/cjw2021/sov-stg

공식 코드

Focusing on what to decode and what to train: SOV Decoding with Specific Target Guided DeNoising and Vision Language Advisor

https://github.com/cjw2021/sov-stg-vla

공식 코드

Focusing on what to decode and what to train: SOV Decoding with Specific Target Guided DeNoising and Vision Language Advisor

https://github.com/ckm3/Deep-Transit

공식 코드

Identify Light-Curve Signals with Deep Learning Based Object Detection Algorithm. I. Transit Detection

https://github.com/ckm3/deep-lc

공식 코드

Identifying Light-curve Signals with a Deep Learning Based Object Detection Algorithm. II. A General Light Curve Classification Framework

https://github.com/cleanlab/cleanlab

공식 코드

ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data

https://github.com/clin1223/vldet

공식 코드

Learning Object-Language Alignments for Open-Vocabulary Object Detection

https://github.com/clinicalml/onboarding_human_ai

공식 코드

Effective Human-AI Teams via Learned Natural Language Rules and Onboarding

https://github.com/cliu2/mtrans

공식 코드

Multimodal Transformer for Automatic 3D Annotation and Object Detection

https://github.com/clobotics/piou

공식 코드

PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments

https://github.com/clovaai/AdamP

공식 코드

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights

https://github.com/clovaai/frostnet

공식 코드

FrostNet: Towards Quantization-Aware Network Architecture Search

https://github.com/clovaai/genas

공식 코드

GeNAS: Neural Architecture Search with Better Generalization

https://github.com/clovaai/overhaul-distillation

공식 코드

A Comprehensive Overhaul of Feature Distillation

https://github.com/clovaai/proxydet

공식 코드

ProxyDet: Synthesizing Proxy Novel Classes via Classwise Mixup for Open-Vocabulary Object Detection

https://github.com/clovaai/rexnet

공식 코드

Rethinking Channel Dimensions for Efficient Model Design

https://github.com/clovaai/wsss-bed

공식 코드

Rethinking Saliency-Guided Weakly-Supervised Semantic Segmentation

https://github.com/clusterformer/clusterformer

공식 코드

ClusterFormer: Clustering As A Universal Visual Learner

https://github.com/clxia12/rt-detrv3

공식 코드

RT-DETRv3: Real-time End-to-End Object Detection with Hierarchical Dense Positive Supervision

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