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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://github.com/Labbeti/SSLH

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Comparison of semi-supervised deep learning algorithms for audio classification

https://github.com/LixiaoTHU/PartImageNetPP

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PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition

https://github.com/MRLoghmani/rcfusion

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Recurrent Convolutional Fusion for RGB-D Object Recognition

https://github.com/Madave94/multi-annotator-toolkit

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Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations

https://github.com/MadryLab/backgrounds_challenge

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Noise or Signal: The Role of Image Backgrounds in Object Recognition

https://github.com/MadryLab/robustness

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Do Adversarially Robust ImageNet Models Transfer Better?

https://github.com/MichaelRamamonjisoa/SharpNet

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SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimation

https://github.com/MoeinSorkhei/glow2

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Full-Glow: Fully conditional Glow for more realistic image generation

https://github.com/NataliaDiaz/Egoshots

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Egoshots, an ego-vision life-logging dataset and semantic fidelity metric to evaluate diversity in image captioning models

https://github.com/PAIR-code/saliency

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Attribution in Scale and Space

https://github.com/PKUAI26/AT-CNN

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Interpreting Adversarially Trained Convolutional Neural Networks

https://github.com/PeizeSun/SparseR-CNN

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Sparse R-CNN: End-to-End Object Detection with Learnable Proposals

https://github.com/PhilJd/freiburg_groceries_dataset

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The Freiburg Groceries Dataset

https://github.com/Pranav21091996/Semantic_Fidelity-and-Egoshots

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Egoshots, an ego-vision life-logging dataset and semantic fidelity metric to evaluate diversity in image captioning models

https://github.com/Rainyfish/FASRGAN-and-Fs-SRGAN

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Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-Resolution

https://github.com/RalphMao/PatchNet

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PatchNet -- Short-range Template Matching for Efficient Video Processing

https://github.com/RosettaWYzhang/AdaPC

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On Automatic Data Augmentation for 3D Point Cloud Classification

https://github.com/RyanCV/BPGrad

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Training Deep Neural Networks via Branch-and-Bound

https://github.com/SenHe/uavdvsm

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Understanding and Visualizing Deep Visual Saliency Models

https://github.com/SensorsINI/v2e

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v2e: From Video Frames to Realistic DVS Events

https://github.com/SeyedAmirTafrishi/LCS_Filter

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Line-Circle-Square (LCS): A Multilayered Geometric Filter for Edge-Based Detection

https://github.com/Sha-Lab/CASTLE

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Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning

https://github.com/Sharath-girish/LTH-ObjectRecognition

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The Lottery Ticket Hypothesis for Object Recognition

https://github.com/Shohan29531/BLV-Road-Nav-Accessibility

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A Dataset for Crucial Object Recognition in Blind and Low-Vision Individuals' Navigation

https://github.com/SiddhantKapil/LA-Transformer

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Person Re-Identification with a Locally Aware Transformer

https://github.com/Simula-COMPLEX/pure

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Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Driving

https://github.com/Smart-Wheelchair-RRC/o3d-sim

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Open-Set 3D Semantic Instance Maps for Vision Language Navigation -- O3D-SIM

https://github.com/Snowfallingplum/rain-streaks-removal

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Directional Regularized Tensor Modeling for Video Rain Streaks Removal

https://github.com/Spandan-Madan/generalization_biased_category_pose

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When and how CNNs generalize to out-of-distribution category-viewpoint combinations

https://github.com/Stry233/Visual-Story-Generation-Based-on-Emotional-and-Keyword-Scheme

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Visual Story Generation Based on Emotion and Keywords

https://github.com/TaISLab/CNN-based-Methods-for-Tactile-Object-Recognition

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CNN-based Methods for Object Recognition with High-Resolution Tactile Sensors

https://github.com/Taccel-Simulator/Taccel

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Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation

https://github.com/ThomasMiconi/HebbianCNNPyTorch

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Hebbian learning with gradients: Hebbian convolutional neural networks with modern deep learning frameworks

https://github.com/ThomasYerxa/mmcr

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Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations

https://github.com/ThrupthiAnn/Canonical-Salient-Maps

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Canonical Saliency Maps: Decoding Deep Face Models

https://github.com/TristHas/GOZ

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On zero-shot recognition of generic objects

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