30 citations · 104 across the 11 of their papers we have counts for
7 papers · 1 filter
Test-Time Training on Video Streams
Renhao Wang, Yu Sun, Arnuv Tandon +4
Prior work has established Test-Time Training (TTT) as a general framework to further improve a trained model at test time. Before making a prediction on each test instance, the mo…
MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Pose
Yang Fu, Ishan Misra, Xiaolong Wang
We propose a generalizable neural radiance fields - MonoNeRF, that can be trained on large-scale monocular videos of moving in static scenes without any ground-truth annotations of…
Joint Hand Motion and Interaction Hotspots Prediction from Egocentric Videos
Shaowei Liu, Subarna Tripathi, Somdeb Majumdar +1
We propose to forecast future hand-object interactions given an egocentric video. Instead of predicting action labels or pixels, we directly predict the hand motion trajectory and…
Look Outside the Room: Synthesizing A Consistent Long-Term 3D Scene Video from A Single Image
Xuanchi Ren, Xiaolong Wang
Novel view synthesis from a single image has recently attracted a lot of attention, and it has been primarily advanced by 3D deep learning and rendering techniques. However, most w…
Accelerating Proposal Generation Network for \\Fast Face Detection on Mobile Devices
Heming Zhang, Xiaolong Wang, Jingwen Zhu +1
Face detection is a widely studied problem over the past few decades. Recently, significant improvements have been achieved via the deep neural network, however, it is still challe…
LCANet: End-to-End Lipreading with Cascaded Attention-CTC
Kai Xu, Dawei Li, Nick Cassimatis +1
Machine lipreading is a special type of automatic speech recognition (ASR) which transcribes human speech by visually interpreting the movement of related face regions including li…
DeepRebirth: Accelerating Deep Neural Network Execution on Mobile Devices
Dawei Li, Xiaolong Wang, Deguang Kong
Deploying deep neural networks on mobile devices is a challenging task. Current model compression methods such as matrix decomposition effectively reduce the deployed model size, b…