arXiv subjects

Mingyang Du

Publications and source records attributed to Mingyang Du.

10 recordsLinked to original sources

arXiv2026

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

High-fidelity 3D generation predominantly relies on scaling model capacity and data, which incurs prohibitive computational costs. This paradigm typically requires learning geometry from scratch and overlooks the rich semantic and structural priors already encapsulated in discriminative 3D foundation models. We contend that leveraging the profound understanding of the 3D world possessed by these discriminative models can significantly reduce generative cost. To this end, we propose ROAD, a framework that reduces the training cost of 3D generation by transferring these rich discriminative priors into diffusion transformers. To address the inherent semantic-structural heterogeneity between generative and discriminative latents, we introduce a reciprocal-objective alignment strategy. This method synergizes Holistic Semantic Condensing to enforce global semantic coherence and Structural Optimal Alignment, which is formulated as a bipartite matching problem to rigorously align microscopic geometric details between disparate latent spaces. The 3D foundation model is only used for training-time supervision of alignment and is not used at inference, incurring no additional inference cost. Compared with the industrial baseline Step1X-3D, the proposed ROAD achieves highly competitive generation performance with only 1.5% of the training data and significantly reduces training costs, effectively reducing the computational overhead of high-fidelity 3D generation. Code is available at https://github.com/H-EmbodVis/ROAD.

cs.CV↗

arXiv2025

More Than Generation: Unifying Generation and Depth Estimation via Text-to-Image Diffusion Models

Generative depth estimation methods leverage the rich visual priors stored in pre-trained text-to-image diffusion models, demonstrating astonishing zero-shot capability. However, parameter updates during training lead to catastrophic degradation in the image generation capability of the pre-trained model. We introduce MERGE, a unified model for image generation and depth estimation, starting from a fixed pre-trained text-to-image model. MERGE demonstrates that the pre-trained text-to-image model can do more than image generation, but also expand to depth estimation effortlessly. Specifically, MERGE introduces a play-and-plug framework that enables seamless switching between image generation and depth estimation modes through simple and pluggable converters. Meanwhile, we propose a Group Reuse Mechanism to encourage parameter reuse and improve the utilization of the additional learnable parameters. MERGE unleashes the powerful depth estimation capability of the pre-trained text-to-image model while preserving its original image generation ability. Compared to other unified models for image generation and depth estimation, MERGE achieves state-of-the-art performance across multiple depth estimation benchmarks. The code will be made available at https://github.com/H-EmbodVis/MERGE

cs.CV↗

arXiv2025

SoccerNet 2025 Challenges Results

The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understanding. This year's challenges span four vision-based tasks: (1) Team Ball Action Spotting, focused on detecting ball-related actions in football broadcasts and assigning actions to teams; (2) Monocular Depth Estimation, targeting the recovery of scene geometry from single-camera broadcast clips through relative depth estimation for each pixel; (3) Multi-View Foul Recognition, requiring the analysis of multiple synchronized camera views to classify fouls and their severity; and (4) Game State Reconstruction, aimed at localizing and identifying all players from a broadcast video to reconstruct the game state on a 2D top-view of the field. Across all tasks, participants were provided with large-scale annotated datasets, unified evaluation protocols, and strong baselines as starting points. This report presents the results of each challenge, highlights the top-performing solutions, and provides insights into the progress made by the community. The SoccerNet Challenges continue to serve as a driving force for reproducible, open research at the intersection of computer vision, artificial intelligence, and sports. Detailed information about the tasks, challenges, and leaderboards can be found at https://www.soccer-net.org, with baselines and development kits available at https://github.com/SoccerNet.

cs.CV↗

arXiv2025

UniFuture: A 4D Driving World Model for Future Generation and Perception

We present UniFuture, a unified 4D Driving World Model designed to simulate the dynamic evolution of the 3D physical world. Unlike existing driving world models that focus solely on 2D pixel-level video generation (lacking geometry) or static perception (lacking temporal dynamics), our approach bridges appearance and geometry to construct a holistic 4D representation. Specifically, we treat future RGB images and depth maps as coupled projections of the same 4D reality and model them jointly within a single framework. To achieve this, we introduce a Dual-Latent Sharing (DLS) scheme, which maps visual and geometric modalities into a shared spatio-temporal latent space, implicitly entangling texture with structure. Furthermore, we propose a Multi-scale Latent Interaction (MLI) mechanism, which enforces bidirectional consistency: geometry constrains visual synthesis to prevent structural hallucinations, while visual semantics refine geometric estimation. During inference, UniFuture can forecast high-fidelity, geometrically consistent 4D scene sequences (image-depth pairs) from a single current frame. Extensive experiments on the nuScenes and Waymo datasets demonstrate that our method outperforms specialized models in both future generation and geometry perception, highlighting the efficacy of unified 4D modeling for autonomous driving. The code is available at https://github.com/dk-liang/UniFuture.

cs.CV↗

arXiv2024

High-temperature Superconductivity in Perovskite Hydride below 10 GPa

Hydrogen and hydrides materials have long been considered promising materials for high-temperature superconductivity. But the extreme pressures required for the metallization of hydrogen-based superconductors limit their applications. Here, we have designed a series of high-temperature perovskite hydrides that can be stable within 10 GPa. Our research covered 182 ternary systems and ultimately determined that 9 compounds were stable within 20 GPa, of which 5 exhibited superconducting transition temperatures exceeding 120 K within 10 GPa. Excitingly, KGaH3 and CsInH3 are thermodynamically stable at 50 GPa. Among these perovskite hydrides, alkali metals are responsible for providing a fixed amount of charge and maintaining structural stability, while the cubic framework formed by IIIA group elements and hydrogen is crucial for high-temperature superconductivity. This work will inspire further experimental exploration and take an important step in the exploration of low-pressure stable high-temperature superconductors.

cond-mat.supr-con↗

arXiv2023

Superconducting phases of YH9 under pressure

Yttrium superhydrides has attracted much attention due to their multiple stoichiometries and excellent superconductivities under high pressure. Especially, YH9 have a Tc of 243 K, which is the second highest Tc among all binary hydrides. It exhibits a positive pressure dependence of Tc below 200 GPa, contrary to the results of theoretical prediction. In order to explore the origin of Tc at low pressure, we extensively investigated the crystal structure of YH9 at different pressure, and found a distorted cage structure with a symmetry of Pnma. This phase has the lowest enthalpy at pressure below 220 GPa, and its X-ray diffraction patterns is consistent with experimental data. Most importantly, the pressure dependence of Tc in phase Pnma is in line with the experimental results. Further calculations show the structural distortion strongly affect the lattice vibration and electron-phonon coupling, leads to the Pnma phase exhibiting a positive pressure dependence of Tc.

cond-mat.supr-con↗

arXiv2022

Pressure-induced high-temperature superconductivity in ternary Y-Zr-H compounds

Compressed hydrogen-rich compounds have received extensive attention as appealing contenders for superconductors, and further challenges are maintaining the stability and superconductivity of hydrides at lower pressures. In this work, we found several novel hydrides YZrH6, YZrH8 and YZrH12 with excellent superconductivity in the Y-Zr-H ternary system. Interestingly, YZrH6 with an A15-type structure can maintain dynamic stability down to 0.01 GPa and still with a critical temperature (Tc) of 16 K. YZrH8 and YZrH12 have high Tc of 70 K and 183 K at 200 GPa and 160 GPa, respectively. The phonon modes associated with H atoms contribute significantly to the electron-phonon coupling, and the H-driven electronic density of states play an important role in superconductivity. These findings highlight relationship between the H-driven electronic density of states, electron-phonon coupling and the superconductivity in a distinct class of hydrides, opening new avenues for designing and optimizing new hydrogen-rich high temperature superconductors.

cond-mat.supr-con↗

arXiv2022

Room-temperature superconductivity in heavy rare earth metal substituted sodalite-like clathrate hexahydrides under moderate pressure

Room temperature superconductivity is a dream that mankind has been chasing for a century. In recent years, the synthesis of H3S, LaH10 and C-S-H system has gradually made this dream a reality. But the extreme pressures required for the metallization of hydrogen-based superconductors limit their applications. In this work, we design a series of high temperature superconductors that can be stable at moderate pressures by incorporating heavy rare earth elements Yb/Lu into sodalite-like clathrate hydrides. In particular, the critical temperatures of Y3LuH24, YLuH12 and YLu3H24 are 283 K, 275 K and 288 K, respectively, which are close to or have reached room temperature, and the required pressure for stabilization of these hydrides is about 120 GPa which is significantly lower than that of reported room temperature superconductors. Our work provides an effective method for the rational design of low-pressure stabilized hydrogen-based superconductors with high-Tc and will stimulate further experimental exploration.

cond-mat.supr-con↗

arXiv2021

Superconductivity of CH4-intercalated H3S under high pressure

The discovery of the high temperature superconducting state in compounds of hydrogen, carbon and sulfur with the critical temperature (Tc) of 288 K at high pressure is an important milestone towards room-temperature superconductors. Here, we have extensively investigated the high-pressure phases of CS2H10, and found four phases Cmc21, P3m1, P-3m1 and Pm. Among them, P3m1 can be dynamically stable at pressure as low as 50 GPa, and Cmc21 has high Tc of 155 K at 150 GPa. Both of Cmc21 and P3m1 are host-guest hydrides, in which CH4 molecules are inserted into Im-3m-H3S and R3m-H3S sublattices, respectively. Their Tc is dominated by the H3S lattice inside. The insertion of CH4 greatly reduces the pressure required for the stability of the original H3S lattice, but it has a negative impact on superconductivity that cannot be ignored. By studying the effect of CH4 insertion in the H3S lattice, we can design hydrides with Tc close to that of H3S and a greatly reduced pressure required for stability.

cond-mat.supr-con↗

arXiv2021

Design Principles for High Temperature Superconductors with Hydrogen-based Alloy Backbone at Moderate Pressure

Hydrogen-based superconductors provide a route to the long-sought goal of room-temperature superconductivity, but the high pressures required to metallize these materials limit their immediate application. For example, carbonaceous sulfur hydride, the first room-temperature superconductor, can reach a critical temperature (Tc) of 288 K only at the extreme pressure of 267 GPa. The next recognized challenge is the realization of room-temperature superconductivity at significantly lower pressures. Here, we propose a strategy for the rational design of high-temperature superconductors at low pressures by alloying small-radius elements and hydrogen to form ternary hydride superconductors with alloy backbones. We identify a hitherto unknown fluorite-type backbone in compositions of the form AXH8, which exhibit high temperature superconductivity at moderate pressures. The Fm-3m phase of LaBeH8, with a fluorite-type H-Be alloy backbone, is predicted to be metastable and superconducting with a Tc ~ 191 K at 50 GPa; a substantially lower pressure than that required by the geometrically similar clathrate hydride LaH10 (170 GPa). Our approach paves the way for finding high-Tc ternary hydride superconductors at conditions close to ambient pressures.

cond-mat.supr-con↗