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首次观测 · 记录 #1CVF · CVPR 2026:cvf:89226e4e3ffca97965bd1772cbdbe529CVF · CVPR 2026

Color-Encoded Illumination for High-Speed Volumetric Scene Reconstruction

Novikov, David, Vaknin, Eilon, Tumanyan, Narek, Sheinin, Mark

原文摘要

The task of capturing and rendering 3D dynamic scenes from 2D images has become increasingly popular in recent years. However, most conventional cameras are bandwidth-limited to 30-60 FPS, restricting these methods to static or slowly evolving scenes. While overcoming bandwidth limitations is difficult in general scenes, recent years have seen a flurry of computational imaging methods that yield high-speed videos using conventional cameras for specific scenarios (e.g., motion capture and particle image velocimetry). However, most of these methods require modifications to camera optics or the addition of mechanically moving components, limiting them to a single-view high-speed capture. Consequently, these cannot be readily used to capture a 3D representation of rapid scene motion. In this paper, we propose a novel method to capture and reconstruct a volumetric representation of a high-speed scene using only unaugmented low-speed cameras. Instead of modifying the hardware or optics of each individual camera, we encode high-speed scene dynamics by illuminating the scene with a rapid, sequential color sequence. This results in simultaneous multi-view capture of the scene, in which high-speed temporal information is encoded in the images' color. To construct a high-speed volumetric representation of the dynamic scene, we develop a novel dynamic Gaussian Splatting-based approach that decodes the temporal information from the images. We evaluate our approach on simulated scenes and real-world experiments using a multi-camera imaging setup, showing first-of-a-kind high-speed volumetric scene reconstructions.

cs.CV

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition · 2026 · 正式发表

首次观测 · 记录 #1CVF · CVPR 2026:cvf:dfc0c9b1e92d13cbf9927f995f702395CVF · CVPR 2026

Hearing the Room Through the Shape of the Drum: Modal-Guided Sound Recovery from Multi-Point Surface Vibrations

Bagon, Shai, Kichler, Matan, Sheinin, Mark

原文摘要

Optical vibration sensing enables recovering the scene sound directly from the surface vibration of nearby objects, turning everyday objects into "visual microphones". However, most prior methods had focused on capturing the vibrations of specific objects with highly favorable vibration responses. These include objects where the surface vibrations are generated by the object itself (e.g., speaker membrane or guitar body) or objects consisting of a thin membrane which is highly reactive to sound (e.g., a chip bag or the leaf of a plant).In this paper, we tackle sound recovery for a more challenging class of solid objects whose vibration responses are poor or highly resonant. We simultaneously capture vibrations for multiple surface points on the object using a speckle-based vibrometry imaging system. Then, we derive a novel physics-guided vibration formation model that relates the scene sound source to the captured multi-point multi-axis vibrations via the object's vibrational modes. The model is then used to reverse the resonant transfer function of the vibrating object, fusing the plurality of vibration signals to estimate the original sound source of the scene. We evaluate our approach by recovering sound from a variety of everyday objects, demonstrating that it significantly outperforms traditional single-point speckle vibrometry in challenging scenarios where it performs poorly.

cs.CV

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition · 2026 · 正式发表