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Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur

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樓主: VER
31#
發(fā)表于 2025-3-26 21:27:12 | 只看該作者
Stereo Event-Based Particle Tracking Velocimetry for 3D Fluid Flow Reconstruction,ate outputs are incorporated into an optimization framework that also includes physically plausible regularizers, in order to retrieve the 3D velocity field. Extensive experiments on both simulated and real data demonstrate the efficacy of our approach.
32#
發(fā)表于 2025-3-27 02:24:18 | 只看該作者
Distance-Normalized Unified Representation for Monocular 3D Object Detection,of the projected 2D corners and centers of 3D boxes, which can be used to recover object physical size and orientation by a projection-consistency loss. Experimental results on the challenging KITTI autonomous driving dataset show that UR3D achieves accurate monocular 3D object detection with a compact architecture.
33#
發(fā)表于 2025-3-27 06:53:10 | 只看該作者
Where to Explore Next? ExHistCNN for History-Aware Autonomous 3D Exploration,N, that estimates the NBV as a set of directions towards which the depth sensor finds most unexplored areas. We perform extensive evaluation on both synthetic and real room scans demonstrating that the proposed ExHistCNN is able to approach the exploration performance of an oracle using the complete knowledge of the 3D environment.
34#
發(fā)表于 2025-3-27 11:42:32 | 只看該作者
35#
發(fā)表于 2025-3-27 15:35:02 | 只看該作者
36#
發(fā)表于 2025-3-27 18:08:47 | 只看該作者
37#
發(fā)表于 2025-3-27 22:09:03 | 只看該作者
Stream Regulation in North Americadate the inherent differences in appearance between real images and DEMs, we train a cross-domain feature descriptor using Structure From Motion (SFM) guided reconstructions to acquire training data. Our method runs efficiently on a mobile device and outperforms existing learned and hand-designed feature descriptors for this task.
38#
發(fā)表于 2025-3-28 04:05:55 | 只看該作者
39#
發(fā)表于 2025-3-28 10:17:40 | 只看該作者
LandscapeAR: Large Scale Outdoor Augmented Reality by Matching Photographs with Terrain Models Usindate the inherent differences in appearance between real images and DEMs, we train a cross-domain feature descriptor using Structure From Motion (SFM) guided reconstructions to acquire training data. Our method runs efficiently on a mobile device and outperforms existing learned and hand-designed feature descriptors for this task.
40#
發(fā)表于 2025-3-28 14:12:44 | 只看該作者
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