arXiv Computer Vision
Can a Display Be Used for Rapid LiDAR-Camera Extrinsic Calibration?
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arXiv Computer Vision
1d ago
FREE-LIVO: Physically Decoupled Yet Tightly Coupled LiDAR-Inertial-Visual Odometry
arXiv:2611.07463v1 Announce Type: cross Abstract: LiDAR-Inertial-Visual Odometry (LIVO) integrates complementary LiDAR, camera, and IMU measurements to achieve robust state estimation. However, most...
arXiv Computer Vision
Aug 25
Simplified Cross-Modal Calibration for Heterogeneous Event-RGB Stereo Systems
arXiv:2608.22965v1 Announce Type: new Abstract: Accurate extrinsic calibration between event-based and frame-based cameras remains a practical bottleneck for heterogeneous stereo systems. Existing ap...
arXiv Computer Vision
5d ago
CalibSwitch: Observation-Driven Camera-LiDAR Extrinsic Recovery and Selective Maintenance for Multimodal Perception
CalibSwitch is an observation‑driven framework for Camera–LiDAR perception that separates absolute extrinsic recovery from selective state maintenance. It introduces a cross‑modal absolute extrinsic generator (CAEG) that recovers full SE(3) candidates from image–point observations without needing an initial transform, and a selective recurrent calibration policy (SRCP) that decides when to update the working geometry based on observation quality and temporal history. On the nuScenes dataset, CAEG achieves mean translation and rotation errors of 0.248 m and 5.884°, while SRCP reduces composite error to 1.46 with only 9.70 % candidate commitments, improving frozen‑detector mAP and NDS by 1.43 and 0.92 points respectively.
arXiv Computer Vision
Oct 27
Metric Scale for Insta360 Structure-from-Motion from the Camera's Embedded IMU
arXiv:2610.35554v1 Announce Type: new Abstract: Structure-from-motion (SfM) from the dual-fisheye video of a consumer 360-degree camera recovers geometry only up to a similarity transform; in the pip...
Hugging Face Trending Papers
Oct 26
Metric Scale for Insta360 Structure-from-Motion from the Camera's Embedded IMU
Structure-from-motion (SfM) from the dual-fisheye video of a consumer 360-degree camera recovers geometry only up to a similarity transform; in the pipeline considered here, metric scale is obtained f...
arXiv Computer Vision
Sep 3
TAPVid-MV: A Benchmark for Tracking Any Point in 3D Across Multiple Views
TAPVid-MV is a new benchmark for tracking any point in 3D across multiple synchronized camera views. It comprises 284 sequences, 1,142 calibrated camera streams, and 109,769 point tracks, covering indoor and outdoor domains and derived from various modalities such as depth, LiDAR, SLAM, and simulation. The dataset is visually verified, and evaluation shows that current multi‑view trackers do not consistently outperform monocular trackers, highlighting geometry recovery as a key bottleneck.