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cs.CV2025

UMAMI: Unifying Masked Autoregressive Models and Deterministic Rendering for View Synthesis

Thanh-Tung Le, Tuan Pham, Tung Nguyen +3

Novel view synthesis (NVS) seeks to render photorealistic, 3D-consistent images of a scene from unseen camera poses given only a sparse set of posed views. Existing deterministic n…

cs.CV2025

GeoDiff: Geometry-Guided Diffusion for Metric Depth Estimation

Tuan Pham, Thanh-Tung Le, Xiaohui Xie +1

We introduce a novel framework for metric depth estimation that enhances pretrained diffusion-based monocular depth estimation (DB-MDE) models with stereo vision guidance. While ex…

cs.CV2025

One Diffusion to Generate Them All

Duong H. Le, Tuan Pham, Sangho Lee +5

We introduce OneDiffusion, a versatile, large-scale diffusion model that seamlessly supports bidirectional image synthesis and understanding across diverse tasks. It enables condit…

cs.CV2025

Diffusion-Guided Gaussian Splatting for Large-Scale Unconstrained 3D Reconstruction and Novel View Synthesis

Niluthpol Chowdhury Mithun, Tuan Pham, Qiao Wang +6

Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. Howe…

cs.CV2024

Preserving Identity with Variational Score for General-purpose 3D Editing

Duong H. Le, Tuan Pham, Aniruddha Kembhavi +3

We present Piva (Preserving Identity with Variational Score Distillation), a novel optimization-based method for editing images and 3D models based on diffusion models. Specificall…

cs.CV2024

Neural NeRF Compression

Tuan Pham, Stephan Mandt

Neural Radiance Fields (NeRFs) have emerged as powerful tools for capturing detailed 3D scenes through continuous volumetric representations. Recent NeRFs utilize feature grids to…