
Deep Learning Superpixel Semantic Segmentation with Transparent Initialization and Sparse Encoder
Even though deep learning greatly improves the performance of semantic s...
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RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs
Although 3D Convolutional Neural Networks (CNNs) are essential for most ...
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Posthoc Calibration of Neural Networks
Calibration of neural networks is a critical aspect to consider when inc...
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Calibration of Neural Networks using Splines
Calibrating neural networks is of utmost importance when employing them ...
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Bidirectional SelfNormalizing Neural Networks
The problem of exploding and vanishing gradients has been a longstandin...
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Improved Gradient based Adversarial Attacks for Quantized Networks
Neural network quantization has become increasingly popular due to effic...
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In Defense of Graph Inference Algorithms for Weakly Supervised Object Localization
Weakly Supervised Object Localization (WSOL) methods have become increas...
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Fast and Differentiable Message Passing for Stereo Vision
Despite the availability of many Markov Random Field (MRF) optimization ...
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Mirror Descent View for Neural Network Quantization
Quantizing large Neural Networks (NN) while maintaining the performance ...
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A Signal Propagation Perspective for Pruning Neural Networks at Initialization
Network pruning is a promising avenue for compressing deep neural networ...
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Learning to Adapt for Stereo
Real world applications of stereo depth estimation require models that a...
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Continual Learning with Tiny Episodic Memories
Learning with less supervision is a major challenge in artificial intell...
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Proximal Meanfield for Neural Network Quantization
Compressing large neural networks by quantizing the parameters, while ma...
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Generalized Range Moves
We consider movemaking algorithms for energy minimization of multilabe...
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SNIP: Singleshot Network Pruning based on Connection Sensitivity
Pruning large neural networks while maintaining the performance is often...
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Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials
Dense conditional random fields (CRFs) with Gaussian pairwise potentials...
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DGPose: Disentangled Semisupervised Deep Generative Models for Human Body Analysis
Deep generative modelling for robust human body analysis is an emerging ...
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Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence
We study the incremental learning problem for the classification task, a...
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Efficient Linear Programming for Dense CRFs
The fully connected conditional random field (CRF) with Gaussian pairwis...
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Iteratively Reweighted Graph Cut for Multilabel MRFs with Nonconvex Priors
While widely acknowledged as highly effective in computer vision, multi...
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Thalaiyasingam Ajanthan
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