Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ivo Duarte
dblp:276/4006
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
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 |
Immersive interaction · 50% Interaction techniques and input · 50% | |
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Immersive interaction
augmented reality interaction |
0.4 | 1 | 2020 | DepthLab: Real-time 3D Interaction with Depth Maps for Mobile Augmented Reality · UIST 2020 |
Interaction techniques and input › sensor-based interaction
depth camera-based interaction |
0.4 | 1 | 2020 | DepthLab: Real-time 3D Interaction with Depth Maps for Mobile Augmented Reality · UIST 2020 |
Virtual and augmented reality › augmented reality
mobile augmented reality |
0.1 | 1 | 2020 | DepthLab: Real-time 3D Interaction with Depth Maps for Mobile Augmented Reality · UIST 2020 |
Methods — techniques the papers use, named apart from their topics
physics-based collision · 0.9geometry-aware rendering · 0.9depth map processing · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | DepthLab: Real-time 3D Interaction with Depth Maps for Mobile Augmented RealityabstractMobile devices with passive depth sensing capabilities are ubiquitous, and recently active depth sensors have become available on some tablets and AR/VR devices. Although real-time depth data is accessible, its rich value to mainstream AR applications has been sorely under-explored. Adoption of depth-based UX has been impeded by the complexity of performing even simple operations with raw depth data, such as detecting intersections or constructing meshes. In this paper, we introduce DepthLab, a software library that encapsulates a variety of depth-based UI/UX paradigms, including geometry-aware rendering (occlusion, shadows), surface interaction behaviors (physics-based collisions, avatar path planning), and visual effects (relighting, 3D-anchored focus and aperture effects). We break down the usage of depth into localized depth, surface depth, and dense depth, and describe our real-time algorithms for interaction and rendering tasks. We present the design process, system, and components of DepthLab to streamline and centralize the development of interactive depth features. We have open-sourced our software at https://github.com/googlesamples/arcore-depth-lab to external developers, conducted performance evaluation, and discussed how DepthLab can accelerate the workflow of mobile AR designers and developers. With DepthLab we aim to help mobile developers to effortlessly integrate depth into their AR experiences and amplify the expression of their creative vision. Ruofei Du, Eric Turner 0001, Maksym Dzitsiuk, Luca Prasso, Ivo Duarte, Jason Dourgarian, João Afonso, Jose Pascoal, Josh Gladstone, Nuno Cruces, Shahram Izadi, Adarsh Kowdle, Konstantine Tsotsos, David Kim 0002 |
UIST | 5 |