The paper proposes a new sequence-to-sequence formulation for multi-view stereo (MVS) that jointly predicts 3D geometry for all input views using a global transformer architecture. It introduces ray‑map embeddings to inject camera parameters into image tokens and a unified global cost volume to capture 3D structure across all views. Experiments on public benchmarks demonstrate state‑of‑the‑art performance, outperforming both traditional MVS and feed‑forward reconstruction baselines.
By Aoxiang Fan, Corentin Dumery, Nicolas Talabot, Pascal Fua
arXiv:2610.32800v1 Announce Type: new
Abstract: Real-world 3D reconstruction pipelines often rely on multi-view images degraded by lossy compression. While compression artifacts have been extensively...
By Dong-hwi Kim, Chaewon Moon, Hojun Song, Dongbeom Kim, Junyeong Jang, Aro Kim, Gahyeon Kim, Heejung Choi, Jehee Kim, Gianella Cravioto, Sohyun Lee, Gyeongjin Choi, EunHye Jeong, Soo Ye Kim, Jaehyup Lee, Sang-hyo Park
Persistent Planar Memory for Video World Models (PPMem) introduces a compact 3D memory system using plane primitives for video world models. By integrating a planar prediction head and Depth Token Fusion into a video diffusion transformer, PPMem jointly generates RGB video and planar geometry, merging them into a persistent plane memory that conditions future video chunks. The resulting memory is highly compact, geometrically explicit, cross-view consistent, and adaptive, outperforming prior 3D-grounded models on DL3DV and RealEstate10K in video quality and depth/normal accuracy.
By Yuze He, Bin Tan, Zelin Gao, Yujun Shen, Yong-Jin Liu, Nan Xue, Yinghao Xu
The paper introduces SVRecon, a generalizable neural surface reconstruction framework that uses sparse volumetric representations to achieve high-resolution 3D reconstruction. It employs a two-stage architecture: first predicting occupied voxels with an occupancy network, then rendering only within those regions using specialized sparse algorithms. This approach allows reconstruction at resolutions up to 512³ on 32 GB hardware, producing smoother and more precise surfaces, especially in sparse-view scenarios.
By Aoxiang Fan, Corentin Dumery, Nicolas Talabot, Ming Xu, Hieu Le, Pascal Fua
3D Gaussian Splatting (3DGS) has achieved remarkable success in real-time novel view synthesis, yet it suffers from severe overfitting under sparse-view settings due to insufficient geometric constraints. While recent methods introduce monocular depth priors to mitigate this, they inherently struggle with scale ambiguity and cross-view inconsistency, leading to defective geometry.
arXiv:2312. 00206v4 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has recently enabled real-time rendering of unbounded 3D scenes for novel view synthesis.
By Haolin Xiong, Sairisheek Muttukuru, Hanyuan Xiao, Rishi Upadhyay, Pradyumna Chari, Yajie Zhao, Achuta Kadambi