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08/16/2023
KernelWarehouse: Towards Parameter-Efficient Dynamic Convolution
Dynamic convolution learns a linear mixture of n static kernels weighted...
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05/23/2023
NORM: Knowledge Distillation via N-to-One Representation Matching
Existing feature distillation methods commonly adopt the One-to-one Repr...
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03/25/2023
Compacting Binary Neural Networks by Sparse Kernel Selection
Binary Neural Network (BNN) represents convolution weights with 1-bit va...
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02/17/2023
3D Human Pose Lifting with Grid Convolution
Existing lifting networks for regressing 3D human poses from 2D single-v...
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09/16/2022
Omni-Dimensional Dynamic Convolution
Learning a single static convolutional kernel in each convolutional laye...
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10/18/2021
Sub-bit Neural Networks: Learning to Compress and Accelerate Binary Neural Networks
In the low-bit quantization field, training Binary Neural Networks (BNNs...
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08/11/2021
Learning Deep Multimodal Feature Representation with Asymmetric Multi-layer Fusion
We propose a compact and effective framework to fuse multimodal features...
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11/25/2020
AccSS3D: Accelerator for Spatially Sparse 3D DNNs
Semantic understanding and completion of real world scenes is a foundati...
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10/17/2020
LID 2020: The Learning from Imperfect Data Challenge Results
Learning from imperfect data becomes an issue in many industrial applica...
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08/18/2020
Knowledge Transfer via Dense Cross-Layer Mutual-Distillation
Knowledge Distillation (KD) based methods adopt the one-way Knowledge Tr...
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07/19/2020
Resolution Switchable Networks for Runtime Efficient Image Recognition
We propose a general method to train a single convolutional neural netwo...
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07/13/2020
PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer
Despite their strong modeling capacities, Convolutional Neural Networks ...
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07/13/2020
Learning to Learn Parameterized Classification Networks for Scalable Input Images
Convolutional Neural Networks (CNNs) do not have a predictable recogniti...
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08/14/2019
Learning Two-View Correspondences and Geometry Using Order-Aware Network
Establishing correspondences between two images requires both local and ...
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08/11/2019
HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions
MobileNets, a class of top-performing convolutional neural network archi...
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07/11/2019
Efficient Semantic Scene Completion Network with Spatial Group Convolution
We introduce Spatial Group Convolution (SGC) for accelerating the comput...
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06/03/2019
Deeply-supervised Knowledge Synergy
Convolutional Neural Networks (CNNs) have become deeper and more complic...
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06/03/2019
A Closed-form Solution to Universal Style Transfer
Universal style transfer tries to explicitly minimize the losses in feat...
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07/06/2017
RON: Reverse Connection with Objectness Prior Networks for Object Detection
We present RON, an efficient and effective framework for generic object ...
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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...
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06/07/2017
Network Sketching: Exploiting Binary Structure in Deep CNNs
Convolutional neural networks (CNNs) with deep architectures have substa...
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02/10/2017
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights
This paper presents incremental network quantization (INQ), a novel meth...
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08/16/2016
Dynamic Network Surgery for Efficient DNNs
Deep learning has become a ubiquitous technology to improve machine inte...
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04/03/2016