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Core AI

3,800 papers (63 classified directly here)

Subtopics

Computer Vision (2,278) Multimodal Learning (1,266) Efficient Computing (180) Interpretability (74) Multi-Modal Learning (55) Foundation Models (35)

Papers per year

1
14
93
291
842
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Papers (including subtopics)

A Reverse Hierarchy Model for Predicting Eye Fixations CVPR 2014
Quality Assessment for Comparing Image Enhancement Algorithms CVPR 2014
Bayesian Active Appearance Models CVPR 2014
Three Guidelines of Online Learning for Large-Scale Visual Recognition CVPR 2014
Relative Parts: Distinctive Parts for Learning Relative Attributes CVPR 2014
Object Classification with Adaptable Regions CVPR 2014
Active Annotation Translation CVPR 2014
Looking Beyond the Visible Scene CVPR 2014
Two-Class Weather Classification CVPR 2014
FAUST: Dataset and Evaluation for 3D Mesh Registration CVPR 2014
T-Linkage: A Continuous Relaxation of J-Linkage for Multi-Model Fitting CVPR 2014
GPS-Tag Refinement using Random Walks with an Adaptive Damping Factor CVPR 2014
Preserving Modes and Messages via Diverse Particle Selection ICML 2014
Third-Order Edge Statistics: Contour Continuation, Curvature, and Cortical Connections NIPS 2013
Reshaping Visual Datasets for Domain Adaptation NIPS 2013
Deep Fisher Networks for Large-Scale Image Classification NIPS 2013
Solving the multi-way matching problem by permutation synchronization NIPS 2013
One-shot learning by inverting a compositional causal process NIPS 2013
Reflection methods for user-friendly submodular optimization NIPS 2013
Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation NIPS 2013
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach NIPS 2013
DeViSE: A Deep Visual-Semantic Embedding Model NIPS 2013
Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation NIPS 2013
Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream NIPS 2013
Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies NIPS 2013