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07/12/2023
Learning Kernel-Modulated Neural Representation for Efficient Light Field Compression
Light field is a type of image data that captures the 3D scene informati...
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06/15/2023
Challenges of Using Real-World Sensory Inputs for Motion Forecasting in Autonomous Driving
Motion forecasting plays a critical role in enabling robots to anticipat...
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04/13/2023
Learning-based Spatial and Angular Information Separation for Light Field Compression
Light fields are a type of image data that capture both spatial and angu...
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03/23/2023
Bayesian Reconstruction of Magnetic Resonance Images using Gaussian Processes
A central goal of modern magnetic resonance imaging (MRI) is to reduce t...
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04/26/2022
Robust Audio-Visual Instance Discrimination via Active Contrastive Set Mining
The recent success of audio-visual representation learning can be largel...
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03/11/2022
DNN Training Acceleration via Exploring GPGPU Friendly Sparsity
The training phases of Deep neural network (DNN) consumes enormous proce...
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03/09/2022
CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction
Vision transformer (ViT) has achieved competitive accuracy on a variety ...
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03/28/2021
TransCenter: Transformers with Dense Queries for Multiple-Object Tracking
Transformer networks have proven extremely powerful for a wide variety o...
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06/15/2019
