EDBT 2026 Demo / reviewers in the wild / expert
Weitao Xiong
dblp:188/1845
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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.
| Artificial intelligence
1 paper |
Video understanding and tracking · 50% 3D vision · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Video understanding and tracking › object tracking
3d object tracking |
0.9 | 1 | 2025 | TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels · NeurIPS 2025 |
Computer vision › 3D vision
camera pose estimation |
0.9 | 1 | 2025 | TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels · NeurIPS 2025 |
Computer vision › Video understanding and tracking › object tracking › 3d object tracking
monocular 3d tracking |
0.9 | 1 | 2025 | TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels · NeurIPS 2025 |
Computer vision › 3D vision › motion estimation › motion correspondence
pixel tracking |
0.9 | 1 | 2025 | TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels · NeurIPS 2025 |
Methods — techniques the papers use, named apart from their topics
tracking upsampler · 0.9optimization-based back-projection · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | TrackingWorld: World-centric Monocular 3D Tracking of Almost All PixelsabstractMonocular 3D tracking aims to capture the long-term motion of pixels in 3D space from a single monocular video and has witnessed rapid progress in recent years. However, we argue that the existing monocular 3D tracking methods still fall short in separating the camera motion from foreground dynamic motion and cannot densely track newly emerging dynamic subjects in the videos. To address these two limitations, we propose TrackingWorld, a novel pipeline for dense 3D tracking of almost all pixels within a world-centric 3D coordinate system. First, we introduce a tracking upsampler that efficiently lifts the arbitrary sparse 2D tracks into dense 2D tracks. Then, to generalize the current tracking methods to newly emerging objects, we apply the upsampler to all frames and reduce the redundancy of 2D tracks by eliminating the tracks in overlapped regions. Finally, we present an efficient optimization-based framework to back-project dense 2D tracks into world-centric 3D trajectories by estimating the camera poses and the 3D coordinates of these 2D tracks. Extensive evaluations on both synthetic and real-world datasets demonstrate that our system achieves accurate and dense 3D tracking in a world-centric coordinate frame. Jiahao Lu 0001, Weitao Xiong, Jiacheng Deng 0002, Zhiyang Dou, Cheng Lin 0001, Sai-Kit Yeung, Yuan Liu 0025 |
NeurIPS | 2 |
| 2017 | A game theory-based development planning approach for weapon system-of-systemsabstractA development planning approach combining game theory and network model is proposed to address the strategy selection and evolution for weapons system-of-systems (WSoS) characterized by an iterative and competitive development process between countries. More specifically, the development planning framework, including game player, strategy definition, and constraints (e.g., time and money), is first described, in which combat network is constructed to present the structure and evolution of WSoS. Next, the selection process of development planning strategy is studied based on damage accumulation and mitigation related to WSoS confrontation. Then, a competitive coevolution algorithm (CEA), reflecting that WSoS evolves along with the strategy selection change, is designed to find the optimal development strategy. Last, an illustrative example is used to demonstrate the feasibility and validity of the proposed approach. Weitao Xiong, Bingfeng Ge, Ke-Wei Yang 0001 |
SMC | 1 |