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Object Recognition

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하위 태스크: 3
평가표: 9
보존된 평가 기록: 31

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

<span style="color:grey; opacity: 0.6">( Image credit: Tensorflow Object Detection API )</span>

코드

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

https://bitbucket.org/dataresearchlab/multiscale_dubuc

공식 코드

Multiscale Dubuc: A New Similarity Measure for Time Series

https://github.com/1adrianb/binary-networks-pytorch

공식 코드

Improved training of binary networks for human pose estimation and image recognition

https://github.com/594422814/CF-VGG

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Real-Time Correlation Tracking via Joint Model Compression and Transfer

https://github.com/82magnolia/ev_tta

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Ev-TTA: Test-Time Adaptation for Event-Based Object Recognition

https://github.com/82magnolia/n_imagenet

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N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras

https://github.com/AbdallahAyman/Imagine2touch

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Imagine2touch: Predictive Tactile Sensing for Robotic Manipulation using Efficient Low-Dimensional Signals

https://github.com/AlonLahav/MeshWalker

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MeshWalker: Deep Mesh Understanding by Random Walks

https://github.com/AzulEye/CNN-Failures

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Why do deep convolutional networks generalize so poorly to small image transformations?

https://github.com/Boazrciasn/Quaternion-Capsule-Networks

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Quaternion Capsule Networks

https://github.com/CBMM/eccentricity

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Do Deep Neural Networks Suffer from Crowding?

https://github.com/CXH-Research/DHAN-SHR

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Dual-Hybrid Attention Network for Specular Highlight Removal

https://github.com/CristianoPatricio/zsl-methods

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ZSpeedL -- Evaluating the Performance of Zero-Shot Learning Methods using Low-Power Devices

https://github.com/DLR-RM/BlenderProc

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https://github.com/DTennant/GPC

공식 코드

Learning Semi-supervised Gaussian Mixture Models for Generalized Category Discovery

https://github.com/DarioFontanel/OWR-VisualDomains

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On the Challenges of Open World Recognitionunder Shifting Visual Domains

https://github.com/DirtyHarryLYL/HAKE-Action-Torch

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HAKE: A Knowledge Engine Foundation for Human Activity Understanding

https://github.com/EavnJeong/Event_Modality_Application

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Expanding Event Modality Applications through a Robust CLIP-Based Encoder

https://github.com/EliSchwartz/DeltaEncoder

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Delta-encoder: an effective sample synthesis method for few-shot object recognition

https://github.com/Fei-Long121/DeepBDC

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Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification

https://github.com/FishYuLi/BalancedGroupSoftmax

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Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax

https://github.com/GauriGupta19/Domain-Generalisation-in-Invariance

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Domain Generalization In Robust Invariant Representation

https://github.com/HighwayWu/SIFT-Reconstruction

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Privacy Leakage of SIFT Features via Deep Generative Model based Image Reconstruction

https://github.com/IBM/BigLittleNet

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Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition

https://github.com/IRVLUTD/FewSOL-DataLoader

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FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IRVLUTD/fewsol-toolkit

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FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IRVLUTD/meta-dataset

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FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments

https://github.com/IVRL/Tempsal

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TempSAL -- Uncovering Temporal Information for Deep Saliency Prediction

https://github.com/JDAI-CV/LIO

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Look-into-Object: Self-supervised Structure Modeling for Object Recognition

https://github.com/JiaRenChang/CoPaNet

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Deep Competitive Pathway Networks

https://github.com/JialianW/Forest_RCNN

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Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation

https://github.com/Jianf-Wang/GRCNN

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Convolutional Neural Networks with Gated Recurrent Connections

https://github.com/Jiaolong/self-supervised-da

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Self-supervised Domain Adaptation for Computer Vision Tasks

https://github.com/KaiyangZhou/Dassl.pytorch

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Domain Generalization: A Survey

https://github.com/KaiyangZhou/mixstyle-release

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MixStyle Neural Networks for Domain Generalization and Adaptation

https://github.com/KaiyuYue/cgnl-network.pytorch

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Compact Generalized Non-local Network

https://github.com/LCSL/incremental_multiclass_RLSC

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Incremental Robot Learning of New Objects with Fixed Update Time

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