activity
20182024
most citedVisual Transformers: Token-based Image Representation and Processing for Computer Vision

380 citations · 923 across the 38 of their papers we have counts for

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Showing 2020Show all

9 papers · 1 filter

cs.SD2020★ 2 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.CV2020

One Shot 3D Photography

Johannes Kopf, Kevin Matzen, Suhib Alsisan +12

3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving…

cs.CV2020

Geometric Correspondence Fields: Learned Differentiable Rendering for 3D Pose Refinement in the Wild

Alexander Grabner, Yaming Wang, Peizhao Zhang +5

We present a novel 3D pose refinement approach based on differentiable rendering for objects of arbitrary categories in the wild. In contrast to previous methods, we make two main…

cs.CV2020★ 380 cited

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…

cs.CV2020★ 22 cited

FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining

Xiaoliang Dai, Alvin Wan, Peizhao Zhang +8

Neural Architecture Search (NAS) yields state-of-the-art neural networks that outperform their best manually-designed counterparts. However, previous NAS methods search for archite…

cs.CV2020★ 29 cited

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

Alvin Wan, Xiaoliang Dai, Peizhao Zhang +9

Differentiable Neural Architecture Search (DNAS) has demonstrated great success in designing state-of-the-art, efficient neural networks. However, DARTS-based DNAS's search space i…

cs.CV2020

Deep Space-Time Video Upsampling Networks

Jaeyeon Kang, Younghyun Jo, Seoung Wug Oh +2

Video super-resolution (VSR) and frame interpolation (FI) are traditional computer vision problems, and the performance have been improving by incorporating deep learning recently.…

cs.CV2020★ 29 cited

SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation

Chenfeng Xu, Bichen Wu, Zining Wang +4

LiDAR point-cloud segmentation is an important problem for many applications. For large-scale point cloud segmentation, the \textit{de facto} method is to project a 3D point cloud…

eess.IV2020★ 2 cited

Learning the Loss Functions in a Discriminative Space for Video Restoration

Younghyun Jo, Jaeyeon Kang, Seoung Wug Oh +3

With more advanced deep network architectures and learning schemes such as GANs, the performance of video restoration algorithms has greatly improved recently. Meanwhile, the loss…