arXiv subjects

Yaoqi Huang

Publications and source records attributed to Yaoqi Huang.

7 recordsLinked to original sources

arXiv2026

What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies

Advances in vision-based sensors and computer vision algorithms have significantly improved the analysis and understanding of traffic scenarios. To facilitate the use of these improvements for road safety, this survey systematically categorizes the critical elements that demand attention in traffic scenarios and comprehensively analyzes available vision-driven tasks and datasets. Compared to existing surveys that focus on isolated domains, our taxonomy categorizes attention-worthy traffic entities into two main groups that are anomalies and normal but critical entities, integrating ten categories and twenty subclasses. It establishes connections between inherently related fields and provides a unified analytical framework. Our survey highlights the analysis of 35 vision-driven tasks and comprehensive examinations and visualizations of 73 available datasets based on the proposed taxonomy. The cross-domain investigation covers the pros and cons of each benchmark with the aim of providing information on standards unification and resource optimization. Our article concludes with a systematic discussion of the existing weaknesses, underlining the potential effects and promising solutions from various perspectives. The integrated taxonomy, comprehensive analysis, and recapitulatory tables serve as valuable contributions to this rapidly evolving field by providing researchers with a holistic overview, guiding strategic resource selection, and highlighting critical research gaps.

cs.CV↗

arXiv2026

Hazard-Aware Traffic Scene Graph Generation

Maintaining situational awareness in complex driving scenarios is challenging. It requires continuously prioritizing attention among extensive scene entities and understanding how prominent hazards might affect the ego vehicle. While existing studies excel at detecting specific semantic categories and visually salient regions, they lack the ability to assess safety-relevance. Meanwhile, the generic spatial predicates either for foreground objects only or for all scene entities modeled by existing scene graphs are inadequate for driving scenarios. To bridge this gap, we introduce a novel task, Traffic Scene Graph Generation, which captures traffic-specific relations between prominent hazards and the ego vehicle. We propose a novel framework that explicitly uses traffic accident data and depth cues to supplement visual features and semantic information for reasoning. The output traffic scene graphs provide intuitive guidelines that stress prominent hazards by color-coding their severity and notating their effect mechanism and relative location to the ego vehicle. We create relational annotations on Cityscapes dataset and evaluate our model on 10 tasks from 5 perspectives. The results in comparative experiments and ablation studies demonstrate our capacity in ego-centric reasoning for hazard-aware traffic scene understanding.

cs.CV↗

arXiv2026

TFusionOcc: T-Primitive Based Object-Centric Multi-Sensor Fusion Framework for 3D Occupancy Prediction

The prediction of 3D semantic occupancy enables autonomous vehicles (AVs) to perceive the fine-grained geometric and semantic scene structure for safe navigation and decision-making. Existing methods mainly rely on either voxel-based representations, which incur redundant computation over empty regions, or on object-centric Gaussian primitives, which are limited in modeling complex, non-convex, and asymmetric structures. In this paper, we present TFusionOcc, a T-primitive-based object-centric multi-sensor fusion framework for 3D semantic occupancy prediction. Specifically, we introduce a family of Students t-distribution-based T-primitives, including the plain T-primitive, T-Superquadric, and deformable T-Superquadric with inverse warping, where the deformable T-Superquadric serves as the key geometry-enhancing primitive. We further develop a unified probabilistic formulation based on the Students t-distribution and the T-mixture model (TMM) to jointly model occupancy and semantics, and design a tightly coupled multi-stage fusion architecture to effectively integrate camera and LiDAR cues. Extensive experiments on nuScenes show state-of-the-art performance, while additional evaluations on nuScenes-C demonstrate strong robustness under most corruption scenarios. The code will be available at: https://github.com/DanielMing123/TFusionOcc

cs.CV↗

arXiv2025

OccCylindrical: Multi-Modal Fusion with Cylindrical Representation for 3D Semantic Occupancy Prediction

The safe operation of autonomous vehicles (AVs) is highly dependent on their understanding of the surroundings. For this, the task of 3D semantic occupancy prediction divides the space around the sensors into voxels, and labels each voxel with both occupancy and semantic information. Recent perception models have used multisensor fusion to perform this task. However, existing multisensor fusion-based approaches focus mainly on using sensor information in the Cartesian coordinate system. This ignores the distribution of the sensor readings, leading to a loss of fine-grained details and performance degradation. In this paper, we propose OccCylindrical that merges and refines the different modality features under cylindrical coordinates. Our method preserves more fine-grained geometry detail that leads to better performance. Extensive experiments conducted on the nuScenes dataset, including challenging rainy and nighttime scenarios, confirm our approach's effectiveness and state-of-the-art performance. The code will be available at: https://github.com/DanielMing123/OccCylindrical

cs.CV↗

arXiv2023

Interfacial Stresses on Droplet Interface Bilayers Using Two Photon Fluorescence Lifetime Imaging Microscopy

Response of lipid bilayers to external mechanical stimuli is an active area of research with implications for fundamental and synthetic cell biology. However, there is a lack of tools for systematically imposing mechanical strains and non-invasively mapping out interfacial (membrane) stress distributions on lipid bilayers. In this article, we report a miniature platform to manipulate model cell membranes in the form of droplet interface bilayers (DIBs), and non-invasively measure spatio-temporally resolved interfacial stresses using two photon fluorescence lifetime imaging of an interfacially active molecular flipper (Flipper-TR). We established the effectiveness of the developed framework by investigating interfacial stresses accompanying three key processes associated with DIBs: thin film drainage between lipid monolayer coated droplets, bilayer formation, and bilayer separation. Interestingly, the measurements also revealed fundamental aspects of DIBs including the existence of a radially decaying interfacial stress distribution post bilayer formation, and the simultaneous build up and decay of stress respectively at the bilayer corner and center during bilayer separation. Finally, utilizing interfacial rheology measurements and MD simulations, we also reveal that the tested molecular flipper is sensitive to membrane fluidity that changes with interfacial stress - expanding the scientific understanding of how molecular motors sense stress.

cond-mat.soft↗

arXiv2022

Influence of Salt on the Formation and Separation of Droplet Interface Bilayers

Phospholipid bilayers are a major component of the cell membrane that is in contact with physiological electrolyte solutions including salt ions. The effect of salt on the phospholipid bilayer mechanics is an active research area due to its implications for cellular function and viability. In this manuscript we utilize droplet interface bilayers(DIBs), a bilayer formed artificially between two aqueous droplets, to unravel the bilayer formation and separation mechanics with a combination of experiments and numerical modelling under the effects of K$^+$, Na$^+$, Li$^+$, Ca$^{2+}$ and Mg$^{2+}$. Initially, we measured the interfacial tension and the interfacial complex viscosity of lipid monolayers at a flat oil-aqueous interface and show that both properties are sensitive to salt concentration, ion size and valency. Subsequently, we measured DIB formation rates and show that the characteristic bilayer formation velocity scales with the ratio of the interfacial tension to the interfacial viscosity. Next, we subjected the system to a step strain by separating the drops in a stepwise manner. By tracking the evolution of the bilayer contact angle and radius, we show that salt influences the bilayer separation mechanics including the decay of the contact angle, the decay of the bilayer radius and the corresponding relaxation time. Finally, we explain the salt effect on the observed bilayer separation by means of a mathematical model comprising of the Young-Laplace equation and an evolution equation.

cond-mat.soft↗

arXiv2020

Surface Energy and Separation Mechanics of Droplet Interface Phospholipid Bilayers

Droplet interface bilayers are a convenient model system to study the physio-chemical properties of phospholipid bilayers, the major component of the cell membrane. The mechanical response of these bilayers to various external mechanical stimuli is an active area of research due to implications for cellular viability and development of artificial cells. In this manuscript we characterize the separation mechanics of droplet interface bilayers under step strain using a combination of experiments and numerical modeling. Initially, we show that the bilayer surface energy can be obtained using principles of energy conservation. Subsequently, we subject the system to a step strain by separating the drops in a step wise manner, and track the evolution of the bilayer contact angle and radius. The relaxation time of the bilayer contact angle and radius, along with the decay magnitude of the bilayer radius were observed to increase with each separation step. By analyzing the forces acting on the bilayer and the rate of separation, we show that the bilayer separates primarily through the peeling process with the dominant resistance to separation coming from viscous dissipation associated with corner flows. Finally, we explain the intrinsic features of the observed bilayer separation by means of a mathematical model comprising of the Young-Laplace equation and an evolution equation. We believe that the reported experimental and numerical results extend the scientific understanding of lipid bilayer mechanics, and that the developed experimental and numerical tools offer a convenient platform to study the mechanics of other types of bilayers.

physics.bio-ph↗