arXiv subjects

Xiaojun Xiang

Publications and source records attributed to Xiaojun Xiang.

7 recordsLinked to original sources

arXiv2026

InSpatio-WorldFM: An Open-Source Real-Time Generative Frame Model

We present InSpatio-WorldFM, an open-source real-time frame model for spatial intelligence. Unlike video-based world models that rely on sequential frame generation and incur substantial latency due to window-level processing, InSpatio-WorldFM adopts a frame-based paradigm that generates each frame independently, enabling low-latency real-time spatial inference. By enforcing multi-view spatial consistency through explicit 3D anchors and implicit spatial memory, the model preserves global scene geometry while maintaining fine-grained visual details across viewpoint changes. We further introduce a progressive three-stage training pipeline that transforms a pretrained image diffusion model into a controllable frame model and finally into a real-time generator through few-step distillation. Experimental results show that InSpatio-WorldFM achieves strong multi-view consistency while supporting interactive exploration on consumer-grade GPUs, providing an efficient alternative to traditional video-based world models for real-time world simulation.

cs.CV↗

arXiv2026

INSPATIO-WORLD: A Real-Time 4D World Simulator via Spatiotemporal Autoregressive Modeling

Building world models with spatial consistency and real-time interactivity remains a fundamental challenge in computer vision. Current video generation paradigms often struggle with a lack of spatial persistence and insufficient visual realism, making it difficult to support seamless navigation in complex environments. To address these challenges, we propose INSPATIO-WORLD, a novel real-time framework capable of recovering and generating high-fidelity, dynamic interactive scenes from a single reference video. At the core of our approach is a Spatiotemporal Autoregressive (STAR) architecture, which enables consistent and controllable scene evolution through two tightly coupled components: Implicit Spatiotemporal Cache aggregates reference and historical observations into a latent world representation, ensuring global consistency during long-horizon navigation; Explicit Spatial Constraint Module enforces geometric structure and translates user interactions into precise and physically plausible camera trajectories. Furthermore, we introduce Joint Distribution Matching Distillation (JDMD). By using real-world data distributions as a regularizing guide, JDMD effectively overcomes the fidelity degradation typically caused by over-reliance on synthetic data. Extensive experiments demonstrate that INSPATIO-WORLD significantly outperforms existing state-of-the-art (SOTA) models in spatial consistency and interaction precision, ranking first among real-time interactive methods on the WorldScore-Dynamic benchmark, and establishing a practical pipeline for navigating 4D environments reconstructed from monocular videos.

cs.CV↗

arXiv2025

GeoTexDensifier: Geometry-Texture-Aware Densification for High-Quality Photorealistic 3D Gaussian Splatting

3D Gaussian Splatting (3DGS) has recently attracted wide attentions in various areas such as 3D navigation, Virtual Reality (VR) and 3D simulation, due to its photorealistic and efficient rendering performance. High-quality reconstrution of 3DGS relies on sufficient splats and a reasonable distribution of these splats to fit real geometric surface and texture details, which turns out to be a challenging problem. We present GeoTexDensifier, a novel geometry-texture-aware densification strategy to reconstruct high-quality Gaussian splats which better comply with the geometric structure and texture richness of the scene. Specifically, our GeoTexDensifier framework carries out an auxiliary texture-aware densification method to produce a denser distribution of splats in fully textured areas, while keeping sparsity in low-texture regions to maintain the quality of Gaussian point cloud. Meanwhile, a geometry-aware splitting strategy takes depth and normal priors to guide the splitting sampling and filter out the noisy splats whose initial positions are far from the actual geometric surfaces they aim to fit, under a Validation of Depth Ratio Change checking. With the help of relative monocular depth prior, such geometry-aware validation can effectively reduce the influence of scattered Gaussians to the final rendering quality, especially in regions with weak textures or without sufficient training views. The texture-aware densification and geometry-aware splitting strategies are fully combined to obtain a set of high-quality Gaussian splats. We experiment our GeoTexDensifier framework on various datasets and compare our Novel View Synthesis results to other state-of-the-art 3DGS approaches, with detailed quantitative and qualitative evaluations to demonstrate the effectiveness of our method in producing more photorealistic 3DGS models.

cs.CV↗

arXiv2025

Quadratic Gaussian Splatting: High Quality Surface Reconstruction with Second-order Geometric Primitives

We propose Quadratic Gaussian Splatting (QGS), a novel representation that replaces static primitives with deformable quadric surfaces (e.g., ellipse, paraboloids) to capture intricate geometry. Unlike prior works that rely on Euclidean distance for primitive density modeling--a metric misaligned with surface geometry under deformation--QGS introduces geodesic distance-based density distributions. This innovation ensures that density weights adapt intrinsically to the primitive curvature, preserving consistency during shape changes (e.g., from planar disks to curved paraboloids). By solving geodesic distances in closed form on quadric surfaces, QGS enables surface-aware splatting, where a single primitive can represent complex curvature that previously required dozens of planar surfels, potentially reducing memory usage while maintaining efficient rendering via fast ray-quadric intersection. Experiments on DTU, Tanks and Temples, and MipNeRF360 datasets demonstrate state-of-the-art surface reconstruction, with QGS reducing geometric error (chamfer distance) by 33% over 2DGS and 27% over GOF on the DTU dataset. Crucially, QGS retains competitive appearance quality, bridging the gap between geometric precision and visual fidelity for applications like robotics and immersive reality.

cs.CV↗

arXiv2025

LookCloser: Frequency-aware Radiance Field for Tiny-Detail Scene

Humans perceive and comprehend their surroundings through information spanning multiple frequencies. In immersive scenes, people naturally scan their environment to grasp its overall structure while examining fine details of objects that capture their attention. However, current NeRF frameworks primarily focus on modeling either high-frequency local views or the broad structure of scenes with low-frequency information, which is limited to balancing both. We introduce FA-NeRF, a novel frequency-aware framework for view synthesis that simultaneously captures the overall scene structure and high-definition details within a single NeRF model. To achieve this, we propose a 3D frequency quantification method that analyzes the scene's frequency distribution, enabling frequency-aware rendering. Our framework incorporates a frequency grid for fast convergence and querying, a frequency-aware feature re-weighting strategy to balance features across different frequency contents. Extensive experiments show that our method significantly outperforms existing approaches in modeling entire scenes while preserving fine details. Project page: https://coscatter.github.io/LookCloser/

cs.CV↗

arXiv2025

New phase space of hardness materials and synergic enhancement of hardness and toughness in superconducting Ti2Co and Ti4Co2X (X = B, C, N, O)

Compared to traditional superhard materials with high electron density and strong covalent bonds, alloy materials mainly composed of metallic bonding structures typically have great toughness and lower hardness. Breaking through the limits of alloy materials is a preface and long term topic, which is of great significance and value for improving the comprehensive mechanical properties of alloy materials. Here, we report on the discovery of a cubic alloy semiconducting material Ti2Co with large Vickers of hardness Hvexp = 6.7 GPa and low fracture toughness of KICexp =1.51 MPa m0.5. Unexpectedly, the former value is nearly triple of the Hvcal = 2.66 GPa predicted by density functional theory (DFT) calculations and the latter value is about one or two orders of magnitude smaller than that of ordinary titanium alloy materials (KICexp = 30-120 MPa m0.5).These specifications place Ti2Co far from the phase space of the known alloy materials, but close to medium hardness materials such as MgO or TiO2. Upon incorporation of oxygen into structural void positions, both values were simultaneously improved for Ti4Co2O to = 9.7 GPa and 2.19 MPa m0.5, respectively. Further DFT calculations on the electron localization function of Ti4Co2X (X = B, C, N, O) vs. the interstitial elements indicate that these simultaneous improvements originate from the coexistence of Ti-Co metallic bonds, the emergence of newly oriented Ti-X covalent bonds, and the increase of electron concentration. Moreover, the large difference between Hvexp and Hvcal of Ti2Co suggests underlying mechanism concerning the absence of the O(16d) or Ti2-O bonds in the O-(Ti2)6 octahedron.Our discovery expands the phase space of alloy materials and illuminates the path of exploring superconducting materials with excellent mechanical performances.

cond-mat.mtrl-sci↗

arXiv2023

Observation of Emergent Superconductivity in the Quantum Spin Hall Insulator Ta2Pd3Te5 via Pressure Manipulation

Quantum Spin Hall (QSH) insulators possess distinct helical in-gap states, enabling their edge states to act as one-dimensional conducting channels when backscattering is prohibited by time-reversal symmetry. However, it remains challenging to achieve high-performance combinations of nontrivial topological QSH states with superconductivity for applications and requires understanding of the complicated underlying mechanisms. Here, our experimental observations for a novel superconducting phase in the pressurized QSH insulator Ta2Pd3Te5 is reported, and the high-pressure phase maintains its original ambient pressure lattice symmetry up to 45 GPa. Our in-situ high-pressure synchrotron X-ray diffraction, electrical transport, infrared reflectance, and Raman spectroscopy measurements, in combination with rigorous theoretical calculations, provide compelling evidence for the association between the superconducting behavior and the abnormal densified phase. The isostructural transition was found to modify the topology of the Fermi surface directly, accompanied by a fivefold amplification of the density of states at 20 GPa compared to ambient pressure, which synergistically fosters the emergence of robust superconductivity. A profound comprehension of the fascinating properties exhibited by the compressed Ta2Pd3Te5 phase is achieved, highlighting the extraordinary potential of van der Waals (vdW) QSH insulators for exploring and investigating high-performance electronic advanced devices under extreme conditions.

cond-mat.mtrl-sci↗