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← Core Methods
Machine Learning
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Core Methods
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Classification
15,289 papers
Papers per year
2000: 2
2001: 14
2002: 21
2003: 28
2004: 28
2005: 26
2006: 94
2007: 93
2008: 90
2009: 93
2010: 134
2011: 112
2012: 160
2013: 290
2014: 239
2015: 258
2016: 456
2017: 682
2018: 1145
2019: 1500
2020: 1638
2021: 1667
2022: 1636
2023: 1685
2024: 1600
2025: 1313
2026: 285
Papers
Temporal Action Localization With Pyramid of Score Distribution Features
CVPR 2016
Multi-Scale Patch Aggregation (MPA) for Simultaneous Detection and Segmentation
CVPR 2016
Deep Region and Multi-Label Learning for Facial Action Unit Detection
CVPR 2016
Unconstrained Face Alignment via Cascaded Compositional Learning
CVPR 2016
Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis
CVPR 2016
ProNet: Learning to Propose Object-Specific Boxes for Cascaded Neural Networks
CVPR 2016
Seeing Behind the Camera: Identifying the Authorship of a Photograph
CVPR 2016
Material Classification Using Raw Time-Of-Flight Measurements
CVPR 2016
HD Maps: Fine-Grained Road Segmentation by Parsing Ground and Aerial Images
CVPR 2016
DAG-Recurrent Neural Networks For Scene Labeling
CVPR 2016
Scene Labeling Using Sparse Precision Matrix
CVPR 2016
Noisy Label Recovery for Shadow Detection in Unfamiliar Domains
CVPR 2016
Online Learning With Bayesian Classification Trees
CVPR 2016
Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network
CVPR 2016
Object Tracking via Dual Linear Structured SVM and Explicit Feature Map
CVPR 2016
Robust, Real-Time 3D Tracking of Multiple Objects With Similar Appearances
CVPR 2016
An Empirical Evaluation of Current Convolutional Architectures' Ability to Manage Nuisance Location and Scale Variability
CVPR 2016
Rolling Rotations for Recognizing Human Actions From 3D Skeletal Data
CVPR 2016
Logistic Boosting Regression for Label Distribution Learning
CVPR 2016
Robust Visual Place Recognition With Graph Kernels
CVPR 2016
Pairwise Linear Regression Classification for Image Set Retrieval
CVPR 2016
Multi-Label Ranking From Positive and Unlabeled Data
CVPR 2016
Recognizing Emotions From Abstract Paintings Using Non-Linear Matrix Completion
CVPR 2016
Random Features for Sparse Signal Classification
CVPR 2016
HyperDepth: Learning Depth From Structured Light Without Matching
CVPR 2016
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