arXiv Computer Vision

PVDepth: Panoramic Video Depth Estimation via Geometry-Aware Spatiotemporal Adaptation

arXiv AI
Oct 27

OmniShowcase: Omnidirectional Subject-Consistent Video Generation from Multi-View Images

OmniShowcase introduces a method for generating omnidirectional videos of a specific subject from a handful of multi‑view images. It combines an automated data‑synthesis pipeline that creates training videos with diverse camera trajectories driven by the subject’s geometry, and a geometry‑conditioning technique that supplies the model with surface‑normal maps reconstructed from the reference views. The authors release Showcase‑4K, a large corpus of 3D‑asset‑based videos with 12 camera motions and 88 trajectory configurations, and ShowcaseBench, a held‑out evaluation set with source meshes and camera parameters.

By Junyeong Ahn, Geonwoo Kim, Kinam Kim, Gihwi Kim, Hoonjin Jung, Hyojin Jang, Jaegul Choo
arXiv AI
Jun 2

A Survey of 3D Reconstruction with Event Cameras

arXiv:2505. 08438v4 Announce Type: replace-cross Abstract: Event cameras are rapidly emerging as powerful vision sensors for 3D reconstruction, uniquely capable of asynchronously capturing per-pixel brightness changes.

By Chuanzhi Xu, Haoxian Zhou, Langyi Chen, Haodong Chen, Zeke Zexi Hu, Zhicheng Lu, Ying Zhou, Vera Chung, Qiang Qu, Weidong Cai
arXiv Computer Vision
Sep 30

MUGEN: Interactive Panoramic World Exploration via Camera Control

MUGEN is a large‑scale real‑world dataset of over 1,300 hours of 4K panoramic videos with rich semantic and geometric annotations, designed to support interactive 360° world exploration. Wan360 is a camera‑controllable panoramic video generation model built on MUGEN, featuring ERP‑aware components (periodic longitude RoPE, ERP‑aware padding, random roll yaw) and a panoramic Plücker embedding for camera motion. Together, they address gaps in data and model support for immersive, temporally coherent 360° video generation along user‑specified camera trajectories.

By Jiaming Tan, Zhen Li, Shuwei Shi, Minggui Teng, Siqi Yang, Yuwei Wu, Bo Zheng, Chuanhao Li, Kaipeng Zhang
arXiv Computer Vision
21h ago

MetricTrail: Revisiting the Power of Metric Depth and Local Optimization for Long-Sequence Streaming 3D Reconstruction

MetricTrail is a streaming system that accurately estimates camera motion and performs dense 3D reconstruction from long monocular videos. It leverages single‑image metric depth to improve trajectory accuracy without retraining the correspondence network or enlarging the optimization window, and uses learned adapters to enhance feature matching with frozen DINOv3 representations. The modular design allows independent upgrades of the depth provider, supports supplied camera intrinsics and calibrated stereo data, and achieves the lowest average trajectory error on KITTI, Oxford Spires, and VBR under RGB‑only protocols while delivering strong dense reconstructions on indoor, outdoor, and in‑the‑wild benchmarks.

By Jingnan Gao, Jiahui Huang, Sven Elflein, Jianhao Zheng, Bingxin Ke, Xiaokang Yang, Yichao Yan, Laura Leal-Taix\'e, Qunjie Zhou, Jiawei Ren, Shengyu Huang