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11/29/2022
Procedural Image Programs for Representation Learning
Learning image representations using synthetic data allows training neur...
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10/18/2022
MaSS: Multi-attribute Selective Suppression
The recent rapid advances in machine learning technologies largely depen...
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05/31/2022
VALHALLA: Visual Hallucination for Machine Translation
Designing better machine translation systems by considering auxiliary in...
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11/30/2021
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data
Pre-training models on Imagenet or other massive datasets of real images...
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08/23/2021
Dynamic Network Quantization for Efficient Video Inference
Deep convolutional networks have recently achieved great success in vide...
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06/14/2021
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data
Most existing works in few-shot learning rely on meta-learning the netwo...
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06/04/2021
RegionViT: Regional-to-Local Attention for Vision Transformers
Vision transformer (ViT) has recently showed its strong capability in ac...
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05/11/2021
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition
Multi-modal learning, which focuses on utilizing various modalities to i...
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04/20/2021
Detector-Free Weakly Supervised Grounding by Separation
Nowadays, there is an abundance of data involving images and surrounding...
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03/27/2021
CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
The recently developed vision transformer (ViT) has achieved promising r...
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03/24/2021
A Broad Study on the Transferability of Visual Representations with Contrastive Learning
Tremendous progress has been made in visual representation learning, not...
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03/02/2021
All at Once Network Quantization via Collaborative Knowledge Transfer
Network quantization has rapidly become one of the most widely used meth...
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11/20/2020
Large Scale Neural Architecture Search with Polyharmonic Splines
Neural Architecture Search (NAS) is a powerful tool to automatically des...
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10/22/2020
Deep Analysis of CNN-based Spatio-temporal Representations for Action Recognition
In recent years, a number of approaches based on 2D CNNs and 3D CNNs hav...
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06/23/2020
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
Neural Architecture Search (NAS) is an open and challenging problem in m...
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12/02/2019
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation
Current state-of-the-art models for video action recognition are mostly ...
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07/10/2018
Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition
In this paper, we propose a novel Convolutional Neural Network (CNN) arc...
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02/08/2018
System G Distributed Graph Database
Motivated by the need to extract knowledge and value from interconnected...
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11/16/2017
