43 citations · 150 across the 24 of their papers we have counts for
9 papers · 1 filter
Controllable and Lossless Non-Autoregressive End-to-End Text-to-Speech
Zhengxi Liu, Qiao Tian, Chenxu Hu +5
Some recent studies have demonstrated the feasibility of single-stage neural text-to-speech, which does not need to generate mel-spectrograms but generates the raw waveforms direct…
Radio2Speech: High Quality Speech Recovery from Radio Frequency Signals
Running Zhao, Jiangtao Yu, Tingle Li +2
Considering the microphone is easily affected by noise and soundproof materials, the radio frequency (RF) signal is a promising candidate to recover audio as it is immune to noise…
The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge Distillation
Zihui Xue, Zhengqi Gao, Sucheng Ren +1
Crossmodal knowledge distillation (KD) extends traditional knowledge distillation to the area of multimodal learning and demonstrates great success in various applications. To achi…
Learning Visual Styles from Audio-Visual Associations
Tingle Li, Yichen Liu, Andrew Owens +1
From the patter of rain to the crunch of snow, the sounds we hear often convey the visual textures that appear within a scene. In this paper, we present a method for learning visua…
MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queries
Tianyuan Zhang, Xuanyao Chen, Yue Wang +2
Accurate and consistent 3D tracking from multiple cameras is a key component in a vision-based autonomous driving system. It involves modeling 3D dynamic objects in complex scenes…
Sound2Synth: Interpreting Sound via FM Synthesizer Parameters Estimation
Zui Chen, Yansen Jing, Shengcheng Yuan +3
Synthesizer is a type of electronic musical instrument that is now widely used in modern music production and sound design. Each parameters configuration of a synthesizer produces…
Training-Free Robust Multimodal Learning via Sample-Wise Jacobian Regularization
Zhengqi Gao, Sucheng Ren, Zihui Xue +2
Multimodal fusion emerges as an appealing technique to improve model performances on many tasks. Nevertheless, the robustness of such fusion methods is rarely involved in the prese…
Self-supervision through Random Segments with Autoregressive Coding (RandSAC)
Tianyu Hua, Yonglong Tian, Sucheng Ren +3
Inspired by the success of self-supervised autoregressive representation learning in natural language (GPT and its variants), and advances in recent visual architecture design with…
FUTR3D: A Unified Sensor Fusion Framework for 3D Detection
Xuanyao Chen, Tianyuan Zhang, Yue Wang +2
Sensor fusion is an essential topic in many perception systems, such as autonomous driving and robotics. Existing multi-modal 3D detection models usually involve customized designs…