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Luyang Tang

10 accepted papers

2026

CLoD-GS: Continuous Level-of-Detail via 3D Gaussian Splatting

ICLR 2026poster

Level of Detail (LoD) is a fundamental technique in real-time computer graphics for managing the rendering costs of complex scenes while preserving visual fidelity. Traditionally, LoD is implemented using discrete levels (DLoD), where multiple, distinct versions of a model are swapped out at differe…

Cited by 0SourcecodeScholar
2025

Compressing Streamable Free-Viewpoint Videos to 0.1 MB per Frame

AAAI 2025technical

The success of 3D Gaussian Splatting (3DGS) in static scenes has inspired numerous attempts to construct Free-Viewpoint Videos (FVVs) of dynamic scenes from multi-view videos. Despite advancements in current techniques, simultaneously achieving photo-realistic view synthesis results, fast on-the-fly…

2025

Instant Gaussian Stream: Fast and Generalizable Streaming of Dynamic Scene Reconstruction via Gaussian Splatting

CVPR 2025highlight

Building Free-Viewpoint Videos in a streaming manner offers the advantage of rapid responsiveness compared to offline training methods, greatly enhancing user experience. However, current streaming approaches face challenges of high per-frame reconstruction time (10s+) and error accumulation, limiti…

2025

LocalDyGS: Multi-view Global Dynamic Scene Modeling via Adaptive Local Implicit Feature Decoupling

ICCV 2025poster

Due to the complex and highly dynamic motions in the real world, synthesizing dynamic videos from multi-view inputs for arbitrary viewpoints is challenging. Previous works based on neural radiance field or 3D Gaussian splatting are limited to modeling fine-scale motion, greatly restricting their app…

Cited by 0SourcePDFScholar
2025

Swift4D: Adaptive divide-and-conquer Gaussian Splatting for compact and efficient reconstruction of dynamic scene

ICLR 2025poster

Novel view synthesis has long been a practical but challenging task, although the introduction of numerous methods to solve this problem, even combining advanced representations like 3D Gaussian Splatting, they still struggle to recover high-quality results and often consume too much storage memory…

Cited by 1SourcePDFScholar
2024

Disentangled Generation and Aggregation for Robust Radiance Fields

ECCV 2024poster

"The utilization of the triplane-based radiance fields has gained attention in recent years due to its ability to effectively disentangle 3D scenes with a high-quality representation and low computation cost. A key requirement of this method is the precise input of camera poses. However, due to the…

2024

Structure Consistent Gaussian Splatting with Matching Prior for Few-shot Novel View Synthesis

NeurIPS 2024poster

Despite the substantial progress of novel view synthesis, existing methods, either based on the Neural Radiance Fields (NeRF) or more recently 3D Gaussian Splatting (3DGS), suffer significant degradation when the input becomes sparse. Numerous efforts have been introduced to alleviate this problem,…

2023

GenS: Generalizable Neural Surface Reconstruction from Multi-View Images

NeurIPS 2023poster

Combining the signed distance function (SDF) and differentiable volume rendering has emerged as a powerful paradigm for surface reconstruction from multi-view images without 3D supervision. However, current methods are impeded by requiring long-time per-scene optimizations and cannot generalize to n…

2022

RECCraft System: Towards Reliable and Efficient Collective Robotic Construction

IROS 2022poster

This research presents a novel Collective Robotic Construction (CRC) system named RECCraft. The RECCraft hardware system is composed of the mobile manipulation vehicles, the cubic blocks, and the folding ramp blocks. Solid connection and easy removal of the blocks are achieved by an electropermanent…

Cited by 4SourceScholar
2021

Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation

ICCV 2021poster

Self-supervised methods play an increasingly important role in monocular depth estimation due to their great potential and low annotation cost. To close the gap with supervised methods, recent works take advantage of extra constraints, e.g., semantic segmentation. However, these methods will inevita…

Cited by 109PDFcodeScholar