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Qi Wang 0105

dblp:19/1924-105 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2024
0000-0001-7774-978XORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 first-author · 2 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 100%
Computer graphics and multimedia
1 paper
Visual content generation and editing · 100%
Artificial intelligence
2 papers
Generative modeling · 57% Robot manipulation · 43%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visual content generation and editing
3d content creation
0.812024
RoomTex: Texturing Compositional Indoor Scenes via Iterative Inpainting · ECCV (68) 2024
Haptics and multimodal interaction
tactile sensing
0.612022
SpecTac: A Visual-Tactile Dual-Modality Sensor Using UV Illumination · ICRA 2022
Haptics and multimodal interaction › tactile sensing
vision-based tactile sensor
0.612022
SpecTac: A Visual-Tactile Dual-Modality Sensor Using UV Illumination · ICRA 2022
Machine learning › Generative modeling
diffusion model
0.212024
RoomTex: Texturing Compositional Indoor Scenes via Iterative Inpainting · ECCV (68) 2024
Robotics › Robot manipulation › tactile sensing › tactile perception
visuo-tactile perception
0.212022
SpecTac: A Visual-Tactile Dual-Modality Sensor Using UV Illumination · ICRA 2022

Methods — techniques the papers use, named apart from their topics

inpainting · 1.5diffusion model · 1.5visual triangulation · 1.1force estimation · 1.1fluorescent markers · 1.1UV illumination · 1.1
YearPublicationVenuePosition
2024 RoomTex: Texturing Compositional Indoor Scenes via Iterative Inpainting
Qi Wang 0105, Ruijie Lu, Xudong Xu, Jingbo Wang 0003, Michael Yu Wang, Bo Dai 0002, Dan Xu 0002
ECCV (68)1
2022 SpecTac: A Visual-Tactile Dual-Modality Sensor Using UV Illumination
abstract
Perceiving the dynamical environment both visually and tactilely is crucial for the survival of animals, and therefore, is considered of importance in robotics research. Recently, there has been an increasing interest in vision-based tactile sensors due to their high sensing resolution and robustness to environmental changes. However, almost all vision-based tactile sensors make only partial use of the camera, specifically, only when contact occurs, and stay idle at other times, which results in a waste of the camera information bandwidth. In this paper, we propose a new visual-tactile dual-modality sensor called SpecTac, which can visually inspect the environment and make tactile observations. The main novelty of the sensor is the use of ultraviolet (UV) LEDs and randomly distributed UV fluorescent markers. When the LEDs are on, those markers will be bright and can easily be distinguished and tracked from the background. Besides, by controlling the on and off of the UV LEDs, due to the switchable visibility of those markers, the sensor will switch between visual and tactile sensing mode. The qualities of tactile and visual perception are evaluated quantitatively by force estimation, visual triangulation and visual feature matching. By combining both modalities into one compact sensor, the information from the camera is better utilized, and it is hoped that the sensor will achieve more flexibility in the motion of the robot arm, especially in tasks where the workspace is narrow.
Qi Wang 0105, Yipai Du, Michael Yu Wang
ICRA1