3DGS-LM: Faster Gaussian-Splatting Optimization with Levenberg-Marquardt
By Naomi Wilson
Posted on: September 25, 2024
We present 3DGS-LM, a new method that accelerates the reconstruction of 3D Gaussian Splatting (3DGS) by replacing its ADAM optimizer with a tailored Levenberg-Marquardt (LM). Existing methods reduce the optimization time by decreasing the number of Gaussians or by improving the implementation of the...
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Training Language Models to Self-Correct via Reinforcement Learning
By Kate Martin
Posted on: September 25, 2024
Self-correction is a highly desirable capability of large language models (LLMs), yet it has consistently been found to be largely ineffective in modern LLMs. Existing approaches for training self-correction either require multiple models or rely on a more capable model or other forms of supervision...
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3DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusion
By Naomi Wilson
Posted on: September 25, 2024
The increasing demand for high-quality 3D assets across various industries necessitates efficient and automated 3D content creation. Despite recent advancements in 3D generative models, existing methods still face challenges with optimization speed, geometric fidelity, and the lack of assets for phy...
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Colorful Diffuse Intrinsic Image Decomposition in the Wild
By Naomi Wilson
Posted on: September 25, 2024
Intrinsic image decomposition aims to separate the surface reflectance and the effects from the illumination given a single photograph. Due to the complexity of the problem, most prior works assume a single-color illumination and a Lambertian world, which limits their use in illumination-aware image...
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CVT-Occ: Cost Volume Temporal Fusion for 3D Occupancy Prediction
By Naomi Wilson
Posted on: September 25, 2024
Vision-based 3D occupancy prediction is significantly challenged by the inherent limitations of monocular vision in depth estimation. This paper introduces CVT-Occ, a novel approach that leverages temporal fusion through the geometric correspondence of voxels over time to improve the accuracy of 3D ...
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Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolution
By Naomi Wilson
Posted on: September 22, 2024
Visual data comes in various forms, ranging from small icons of just a few pixels to long videos spanning hours. Existing multi-modal LLMs usually standardize these diverse visual inputs to a fixed resolution for visual encoders and yield similar numbers of tokens for LLMs. This approach is non-opti...
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