research
∙
12/21/2021
Transferable End-to-end Room Layout Estimation via Implicit Encoding
We study the problem of estimating room layouts from a single panorama i...
share
research
∙
08/09/2021
P-WAE: Generalized Patch-Wasserstein Autoencoder for Anomaly Screening
To mitigate the inspector's workload and improve the quality of the prod...
research
∙
01/28/2021
The Tight Bound for Pure Price of Anarchy in an Extended Miner's Dilemma Game
Pool block withholding attack is performed among mining pools in digital...
research
∙
11/25/2020
AccSS3D: Accelerator for Spatially Sparse 3D DNNs
Semantic understanding and completion of real world scenes is a foundati...
research
∙
10/17/2020
LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
research
∙
07/04/2020
On Connections between Regularizations for Improving DNN Robustness
This paper analyzes regularization terms proposed recently for improving...
research
∙
05/23/2020
Adversarial Attack on Hierarchical Graph Pooling Neural Networks
Recent years have witnessed the emergence and development of graph neura...
research
∙
08/14/2019
Learning Two-View Correspondences and Geometry Using Order-Aware Network
Establishing correspondences between two images requires both local and ...
research
∙
07/11/2019
Efficient Semantic Scene Completion Network with Spatial Group Convolution
We introduce Spatial Group Convolution (SGC) for accelerating the comput...
research
∙
07/08/2019
CHOP: Bypassing Runtime Bounds Checking Through Convex Hull OPtimization
Unsafe memory accesses in programs written using popular programming lan...
research
∙
06/03/2019
A Closed-form Solution to Universal Style Transfer
Universal style transfer tries to explicitly minimize the losses in feat...
research
∙
04/19/2019
Deep Likelihood Network for Image Restoration with Multiple Degradations
Convolutional neural networks have been proven very effective in a varie...
research
∙
10/23/2018
Sparse DNNs with Improved Adversarial Robustness
Deep neural networks (DNNs) are computationally/memory-intensive and vul...
research
∙
09/25/2018
Object Detection from Scratch with Deep Supervision
We propose Deeply Supervised Object Detectors (DSOD), an object detectio...
research
∙
08/16/2018
Network Decoupling: From Regular to Depthwise Separable Convolutions
Depthwise separable convolution has shown great efficiency in network de...
research
∙
06/13/2018
Learning Visual Knowledge Memory Networks for Visual Question Answering
Visual question answering (VQA) requires joint comprehension of images a...
research
∙
08/03/2017
DSOD: Learning Deeply Supervised Object Detectors from Scratch
We present Deeply Supervised Object Detector (DSOD), a framework that ca...
research
∙
08/03/2017
Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization
Low-bit deep neural networks (DNNs) become critical for embedded applica...
research
∙
07/06/2017
RON: Reverse Connection with Objectness Prior Networks for Object Detection
We present RON, an efficient and effective framework for generic object ...
research
∙
07/03/2017
Physics Inspired Optimization on Semantic Transfer Features: An Alternative Method for Room Layout Estimation
In this paper, we propose an alternative method to estimate room layouts...
research
∙
06/07/2017
Network Sketching: Exploiting Binary Structure in Deep CNNs
Convolutional neural networks (CNNs) with deep architectures have substa...
research
∙
04/05/2017
Weakly Supervised Dense Video Captioning
This paper focuses on a novel and challenging vision task, dense video c...
research
∙
02/10/2017
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights
This paper presents incremental network quantization (INQ), a novel meth...
research
∙
08/16/2016
Dynamic Network Surgery for Efficient DNNs
Deep learning has become a ubiquitous technology to improve machine inte...
research
∙
04/03/2016
HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection
Almost all of the current top-performing object detection networks emplo...
research
∙
09/08/2015
Deep Attributes from Context-Aware Regional Neural Codes
Recently, many researches employ middle-layer output of convolutional ne...
research
∙
07/06/2014
