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09/08/2022
Cross-Modal Knowledge Transfer Without Task-Relevant Source Data
Cost-effective depth and infrared sensors as alternatives to usual RGB s...
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10/19/2021
Learning Equivariances and Partial Equivariances from Data
Group equivariant Convolutional Neural Networks (G-CNNs) constrain featu...
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12/08/2020
Rotation-Invariant Autoencoders for Signals on Spheres
Omnidirectional images and spherical representations of 3D shapes cannot...
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12/07/2020
Model Compression Using Optimal Transport
Model compression methods are important to allow for easier deployment o...
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12/05/2020
Multi-head Knowledge Distillation for Model Compression
Several methods of knowledge distillation have been developed for neural...
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12/05/2020
Knowledge Distillation Thrives on Data Augmentation
Knowledge distillation (KD) is a general deep neural network training fr...
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12/03/2020
Recovering Trajectories of Unmarked Joints in 3D Human Actions Using Latent Space Optimization
Motion capture (mocap) and time-of-flight based sensing of human actions...
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06/18/2020
Generative Patch Priors for Practical Compressive Image Recovery
In this paper, we propose the generative patch prior (GPP) that defines ...
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06/13/2019
Temporal Transformer Networks: Joint Learning of Invariant and Discriminative Time Warping
Many time-series classification problems involve developing metrics that...
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09/08/2018
Rate-Adaptive Neural Networks for Spatial Multiplexers
In resource-constrained environments, one can employ spatial multiplexin...
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06/08/2018
CS-VQA: Visual Question Answering with Compressively Sensed Images
Visual Question Answering (VQA) is a complex semantic task requiring bot...
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01/26/2016
