activity
20162023
most citedSqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

57 citations · 257 across the 18 of their papers we have counts for

collaborators
Showing 2020Show all

11 papers · 1 filter

cs.SD20202 cited

FBWave: Efficient and Scalable Neural Vocoders for Streaming Text-To-Speech on the Edge

Bichen Wu, Qing He, Peizhao Zhang +3

Nowadays more and more applications can benefit from edge-based text-to-speech (TTS). However, most existing TTS models are too computationally expensive and are not flexible enoug…

cs.CV20202 cited

FP-NAS: Fast Probabilistic Neural Architecture Search

Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang +3

Differential Neural Architecture Search (NAS) requires all layer choices to be held in memory simultaneously; this limits the size of both search space and final architecture. In c…

cs.CV202023 cited

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Sicheng Zhao, Xiangyu Yue, Shanghang Zhang +8

Large-scale labeled training datasets have enabled deep neural networks to excel across a wide range of benchmark vision tasks. However, in many applications, it is prohibitively e…

cs.CV2020

ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation

Sicheng Zhao, Yezhen Wang, Bo Li +5

Due to its robust and precise distance measurements, LiDAR plays an important role in scene understanding for autonomous driving. Training deep neural networks (DNNs) on LiDAR data…

cs.CV2020

CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAs

Zhen Dong, Dequan Wang, Qijing Huang +6

Deploying deep learning models on embedded systems has been challenging due to limited computing resources. The majority of existing work focuses on accelerating image classificati…

cs.CV2020

Visual Transformers: Token-based Image Representation and Processing for Computer Vision

Bichen Wu, Chenfeng Xu, Xiaoliang Dai +7

Computer vision has achieved remarkable success by (a) representing images as uniformly-arranged pixel arrays and (b) convolving highly-localized features. However, convolutions tr…