Search Results for author:
Found 11 papers, 5 papers with code
SPOT: Selective Point Cloud Voting for Better Proposal in Point Cloud Object Detection
The sparsity of point clouds limits deep learning models on capturing long-range dependencies, which makes features extracted by the models ambiguous.
TransFace: Unit-Based Audio-Visual Speech Synthesizer for Talking Head Translation
However, talking head translation, converting audio-visual speech (i. e., talking head video) from one language into another, still confronts several challenges compared to audio speech: (1) Existing methods invariably rely on cascading, synthesizing via both audio and text, resulting in delays and cascading errors.
Distilling Coarse-to-Fine Semantic Matching Knowledge for Weakly Supervised 3D Visual Grounding
To accomplish this, we design a novel semantic matching model that analyzes the semantic similarity between object proposals and sentences in a coarse-to-fine manner.
OpenSR: Open-Modality Speech Recognition via Maintaining Multi-Modality Alignment
We demonstrate that OpenSR enables modality transfer from one to any in three different settings (zero-, few- and full-shot), and achieves highly competitive zero-shot performance compared to the existing few-shot and full-shot lip-reading methods.
AV-TranSpeech: Audio-Visual Robust Speech-to-Speech Translation
Direct speech-to-speech translation (S2ST) aims to convert speech from one language into another, and has demonstrated significant progress to date.
Connecting Multi-modal Contrastive Representations
This paper proposes a novel training-efficient method for learning MCR without paired data called Connecting Multi-modal Contrastive Representations (C-MCR).
MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream Mixup for Visual Speech Translation and Recognition
However, despite researchers exploring cross-lingual translation techniques such as machine translation and audio speech translation to overcome language barriers, there is still a shortage of cross-lingual studies on visual speech.
Exploring Group Video Captioning with Efficient Relational Approximation
In this study, we propose a new task, group video captioning, which aims to infer the desired content among a group of target videos and describe it with another group of related reference videos.
Motion Planning Transformers: A Motion Planning Framework for Mobile Robots
A popular technique to improve the efficiency of these planners is to restrict search space in the planning domain.
MPC-MPNet: Model-Predictive Motion Planning Networks for Fast, Near-Optimal Planning under Kinodynamic Constraints
Kinodynamic Motion Planning (KMP) is to find a robot motion subject to concurrent kinematics and dynamics constraints.
