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09/08/2023
On the Efficacy of Multi-scale Data Samplers for Vision Applications
Multi-scale resolution training has seen an increased adoption across mu...
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09/02/2023
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large Language Models
Since Large Language Models or LLMs have demonstrated high-quality perfo...
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05/31/2023
Bytes Are All You Need: Transformers Operating Directly On File Bytes
Modern deep learning approaches usually transform inputs into a modality...
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03/15/2023
Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement
We propose Dataset Reinforcement, a strategy to improve a dataset once s...
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12/20/2022
RangeAugment: Efficient Online Augmentation with Range Learning
State-of-the-art automatic augmentation methods (e.g., AutoAugment and R...
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07/21/2022
SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic Networks
Recent isotropic networks, such as ConvMixer and vision transformers, ha...
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06/06/2022
Separable Self-attention for Mobile Vision Transformers
Mobile vision transformers (MobileViT) can achieve state-of-the-art perf...
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06/04/2022
CVNets: High Performance Library for Computer Vision
We introduce CVNets, a high-performance open-source library for training...
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10/08/2021
LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time
When deploying deep learning models to a device, it is traditionally ass...
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10/08/2021
Token Pooling in Vision Transformers
Despite the recent success in many applications, the high computational ...
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10/05/2021
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
Light-weight convolutional neural networks (CNNs) are the de-facto for m...
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08/28/2021
DKM: Differentiable K-Means Clustering Layer for Neural Network Compression
Deep neural network (DNN) model compression for efficient on-device infe...
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02/20/2021
Learning Neural Network Subspaces
Recent observations have advanced our understanding of the neural networ...
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11/18/2020
Layer-Wise Data-Free CNN Compression
We present an efficient method for compressing a trained neural network ...
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06/26/2020
Supermasks in Superposition
We present the Supermasks in Superposition (SupSup) model, capable of se...
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11/29/2019
What's Hidden in a Randomly Weighted Neural Network?
Training a neural network is synonymous with learning the values of the ...
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11/27/2019
DeFINE: DEep Factorized INput Word Embeddings for Neural Sequence Modeling
For sequence models with large word-level vocabularies, a majority of ne...
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06/12/2019
Assisted Excitation of Activations: A Learning Technique to Improve Object Detectors
We present a simple and effective learning technique that significantly ...
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06/08/2019
DiCENet: Dimension-wise Convolutions for Efficient Networks
In this paper, we propose a new CNN model DiCENet, that is built using: ...
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06/05/2019
Butterfly Transform: An Efficient FFT Based Neural Architecture Design
In this paper, we introduce the Butterfly Transform (BFT), a light weigh...
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06/03/2019
Discovering Neural Wirings
The success of neural networks has driven a shift in focus from feature ...
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05/31/2019
OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge
Visual Question Answering (VQA) in its ideal form lets us study reasonin...
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04/11/2019
Two Body Problem: Collaborative Visual Task Completion
Collaboration is a necessary skill to perform tasks that are beyond one ...
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12/13/2018
ELASTIC: Improving CNNs with Instance Specific Scaling Policies
Scale variation has been a challenge from traditional to modern approach...
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12/03/2018
Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning
Learning is an inherently continuous phenomenon. When humans learn a new...
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11/28/2018
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
We introduce a light-weight, power efficient, and general purpose convol...
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08/27/2018
Pyramidal Recurrent Unit for Language Modeling
LSTMs are powerful tools for modeling contextual information, as evidenc...
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05/07/2018
Label Refinery: Improving ImageNet Classification through Label Progression
Among the three main components (data, labels, and models) of any superv...
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03/19/2018
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
We introduce a fast and efficient convolutional neural network, ESPNet, ...
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12/09/2017
IQA: Visual Question Answering in Interactive Environments
We introduce Interactive Question Answering (IQA), the task of answering...
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11/20/2016
LCNN: Lookup-based Convolutional Neural Network
Porting state of the art deep learning algorithms to resource constraine...
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09/29/2016
CNN-aware Binary Map for General Semantic Segmentation
In this paper we introduce a novel method for general semantic segmentat...
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03/17/2016
"What happens if..." Learning to Predict the Effect of Forces in Images
What happens if one pushes a cup sitting on a table toward the edge of t...
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03/16/2016
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
We propose two efficient approximations to standard convolutional neural...
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12/24/2015
G-CNN: an Iterative Grid Based Object Detector
We introduce G-CNN, an object detection technique based on CNNs which wo...
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12/13/2015
Action Recognition with Image Based CNN Features
Most of human actions consist of complex temporal compositions of more s...
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11/12/2015
Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images
In this paper, we study the challenging problem of predicting the dynami...
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05/05/2014
Comparing apples to apples in the evaluation of binary coding methods
We discuss methodological issues related to the evaluation of unsupervis...
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10/16/2012
