conftrace_
← Topics

Deep Learning

66,648 papers (25 classified directly here)

Subtopics

Learning Types (28,663) Architectures (27,448) Models (16,617) Techniques (8,241) Optimization & Theory (6,829) Application Areas (46)

Papers per year

2
65
428
6150
10854
'05
'10
'15
'20
'25

Papers (including subtopics)

benefits of depth in neural networks COLT 2016
Deep Compositional Captioning: Describing Novel Object Categories Without Paired Training Data CVPR 2016
Stacked Attention Networks for Image Question Answering CVPR 2016
Image Question Answering Using Convolutional Neural Network With Dynamic Parameter Prediction CVPR 2016
Neural Module Networks CVPR 2016
Latent Embeddings for Zero-Shot Classification CVPR 2016
Learning Attributes Equals Multi-Source Domain Generalization CVPR 2016
Anticipating Visual Representations From Unlabeled Video CVPR 2016
Learning to Assign Orientations to Feature Points CVPR 2016
Learning Dense Correspondence via 3D-Guided Cycle Consistency CVPR 2016
Face Alignment Across Large Poses: A 3D Solution CVPR 2016
Affinity CNN: Learning Pixel-Centric Pairwise Relations for Figure/Ground Embedding CVPR 2016
Weakly Supervised Object Boundaries CVPR 2016
Object Contour Detection With a Fully Convolutional Encoder-Decoder Network CVPR 2016
What Value Do Explicit High Level Concepts Have in Vision to Language Problems? CVPR 2016
Learning Relaxed Deep Supervision for Better Edge Detection CVPR 2016
Occlusion Boundary Detection via Deep Exploration of Context CVPR 2016
SemiContour: A Semi-Supervised Learning Approach for Contour Detection CVPR 2016
InterActive: Inter-Layer Activeness Propagation CVPR 2016
Exploit Bounding Box Annotations for Multi-Label Object Recognition CVPR 2016
TI-Pooling: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks CVPR 2016
Fashion Style in 128 Floats: Joint Ranking and Classification Using Weak Data for Feature Extraction CVPR 2016
Compact Bilinear Pooling CVPR 2016
Deep Interactive Object Selection CVPR 2016
ReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements CVPR 2016