Papers with Code 아카이브

Object Detection

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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/boschresearch/hyp-ow

공식 코드

Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection

https://github.com/boschresearch/metanas

공식 코드

Meta-Learning of Neural Architectures for Few-Shot Learning

https://github.com/bosszhe/emiff

공식 코드

EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection

https://github.com/bosszhe/vimi

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VIMI: Vehicle-Infrastructure Multi-view Intermediate Fusion for Camera-based 3D Object Detection

https://github.com/bowen-upenn/Multi-Agent-VQA

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Multi-Agent VQA: Exploring Multi-Agent Foundation Models in Zero-Shot Visual Question Answering

https://github.com/bowenc0221/Decoupled-Classification-Refinement

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Decoupled Classification Refinement: Hard False Positive Suppression for Object Detection

https://github.com/bozcani/COSMO

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COSMO: Contextualized Scene Modeling with Boltzmann Machines

https://github.com/bradleybin/locate-globally-segment-locally-a-progressive-architecture-with-knowledge-review-network-for-sod

공식 코드

Learning Video Salient Object Detection Progressively from Unlabeled Videos

https://github.com/bravegroup/dcd

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Densely Constrained Depth Estimator for Monocular 3D Object Detection

https://github.com/bravegroup/fullysparsefusion

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Fully Sparse Fusion for 3D Object Detection

https://github.com/bravegroup/pointsam-for-mixsup

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MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection

https://github.com/bravezzzzzz/iou-enhanced-attention

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IoU-Enhanced Attention for End-to-End Task Specific Object Detection

https://github.com/bravezzzzzz/recursivedet

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RecursiveDet: End-to-End Region-based Recursive Object Detection

https://github.com/brian-h-wang/pseudolidar-tree-detection

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Detecting and Mapping Trees in Unstructured Environments with a Stereo Camera and Pseudo-Lidar

https://github.com/brycexu/BNN_Kernel

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A Computing Kernel for Network Binarization on PyTorch

https://github.com/bupt-ai-cz/wuda

공식 코드

WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain Labels

https://github.com/bwittmann/transoar

공식 코드

Focused Decoding Enables 3D Anatomical Detection by Transformers

https://github.com/byangderek/CCF

공식 코드

Convolutional Channel Features

https://github.com/byangderek/CRAFT

공식 코드

CRAFT Objects from Images

https://github.com/bytedance/dq-det

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Learning Dynamic Query Combinations for Transformer-based Object Detection and Segmentation

https://github.com/bytedance/ibot

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iBOT: Image BERT Pre-Training with Online Tokenizer

https://github.com/bytedance/kmax-deeplab

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kMaX-DeepLab: k-means Mask Transformer

https://github.com/caddyless/ailurus

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AiluRus: A Scalable ViT Framework for Dense Prediction

https://github.com/caiguohui123/msdet

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MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule

https://github.com/caiqi/cascasde-3d

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3D Cascade RCNN: High Quality Object Detection in Point Clouds

https://github.com/caiqi/sample-weighting-network

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Learning a Unified Sample Weighting Network for Object Detection

https://github.com/caiyingfeng/vrso

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VRSO: Visual-Centric Reconstruction for Static Object Annotation

https://github.com/caiyuanhao1998/retinexformer

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Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement

https://github.com/calayzhou/iod-video

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Explore Spatio-temporal Aggregation for Insubstantial Object Detection: Benchmark Dataset and Baseline

https://github.com/camma-public/cholectrack20

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CholecTrack20: A Dataset for Multi-Class Multiple Tool Tracking in Laparoscopic Surgery

https://github.com/camma-public/cholectriplet2022

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CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection

https://github.com/camma-public/endoscapes

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The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark

https://github.com/camma-public/selfsupsurg

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Dissecting Self-Supervised Learning Methods for Surgical Computer Vision

https://github.com/cancam/LRP

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Localization Recall Precision (LRP): A New Performance Metric for Object Detection

https://github.com/canerozer/explainable-iqa

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Explainable Image Quality Assessment for Medical Imaging

https://github.com/cangumeli/ROCA

공식 코드

ROCA: Robust CAD Model Retrieval and Alignment from a Single Image

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