2 citations · 5 across the 8 of their papers we have counts for
8 papers
OpenM3D: Open Vocabulary Multi-view Indoor 3D Object Detection without Human Annotations
Peng-Hao Hsu, Ke Zhang, Fu-En Wang +6
Open-vocabulary (OV) 3D object detection is an emerging field, yet its exploration through image-based methods remains limited compared to 3D point cloud-based methods. We introduc…
V-MIND: Building Versatile Monocular Indoor 3D Detector with Diverse 2D Annotations
Jin-Cheng Jhang, Tao Tu, Fu-En Wang +3
The field of indoor monocular 3D object detection is gaining significant attention, fueled by the increasing demand in VR/AR and robotic applications. However, its advancement is i…
DreaMo: Articulated 3D Reconstruction From A Single Casual Video
Tao Tu, Ming-Feng Li, Chieh Hubert Lin +3
Articulated 3D reconstruction has valuable applications in various domains, yet it remains costly and demands intensive work from domain experts. Recent advancements in template-fr…
ImGeoNet: Image-induced Geometry-aware Voxel Representation for Multi-view 3D Object Detection
Tao Tu, Shun-Po Chuang, Yu-Lun Liu +5
We propose ImGeoNet, a multi-view image-based 3D object detection framework that models a 3D space by an image-induced geometry-aware voxel representation. Unlike previous methods…
Learning Better Visual Dialog Agents with Pretrained Visual-Linguistic Representation
Tao Tu, Qing Ping, Govind Thattai +2
GuessWhat?! is a two-player visual dialog guessing game where player A asks a sequence of yes/no questions (Questioner) and makes a final guess (Guesser) about a target object in a…
Semi-supervised Learning for Multi-speaker Text-to-speech Synthesis Using Discrete Speech Representation
Tao Tu, Yuan-Jui Chen, Alexander H. Liu +1
Recently, end-to-end multi-speaker text-to-speech (TTS) systems gain success in the situation where a lot of high-quality speech plus their corresponding transcriptions are availab…
Towards Unsupervised Speech Recognition and Synthesis with Quantized Speech Representation Learning
Alexander H. Liu, Tao Tu, Hung-yi Lee +1
In this paper we propose a Sequential Representation Quantization AutoEncoder (SeqRQ-AE) to learn from primarily unpaired audio data and produce sequences of representations very c…
End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning
Tao Tu, Yuan-Jui Chen, Cheng-chieh Yeh +1
End-to-end text-to-speech (TTS) has shown great success on large quantities of paired text plus speech data. However, laborious data collection remains difficult for at least 95% o…