Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Dunn, Enrique"'
Autor:
Min, Zhixiang, Zhuang, Bingbing, Schulter, Samuel, Liu, Buyu, Dunn, Enrique, Chandraker, Manmohan
Monocular 3D object localization in driving scenes is a crucial task, but challenging due to its ill-posed nature. Estimating 3D coordinates for each pixel on the object surface holds great potential as it provides dense 2D-3D geometric constraints f
Externí odkaz:
http://arxiv.org/abs/2305.17763
In this paper, we propose an end-to-end framework that jointly learns keypoint detection, descriptor representation and cross-frame matching for the task of image-based 3D localization. Prior art has tackled each of these components individually, pur
Externí odkaz:
http://arxiv.org/abs/2212.04575
Autor:
Dibene, Juan C., Dunn, Enrique
We present a HoloLens 2 server application for streaming device data via TCP in real time. The server can stream data from the four grayscale cameras, depth sensor, IMU, front RGB camera, microphone, head tracking, eye tracking, and hand tracking. Ea
Externí odkaz:
http://arxiv.org/abs/2211.02648
Autor:
Min, Zhixiang, Khosravan, Naji, Bessinger, Zachary, Narayana, Manjunath, Kang, Sing Bing, Dunn, Enrique, Boyadzhiev, Ivaylo
We present LASER, an image-based Monte Carlo Localization (MCL) framework for 2D floor maps. LASER introduces the concept of latent space rendering, where 2D pose hypotheses on the floor map are directly rendered into a geometrically-structured laten
Externí odkaz:
http://arxiv.org/abs/2204.00157
Autor:
Xu, Xiangyu, Dunn, Enrique
We present GTT-Net, a supervised learning framework for the reconstruction of sparse dynamic 3D geometry. We build on a graph-theoretic formulation of the generalized trajectory triangulation problem, where non-concurrent multi-view imaging geometry
Externí odkaz:
http://arxiv.org/abs/2109.03408
We propose a dense indirect visual odometry method taking as input externally estimated optical flow fields instead of hand-crafted feature correspondences. We define our problem as a probabilistic model and develop a generalized-EM formulation for t
Externí odkaz:
http://arxiv.org/abs/2104.06789
Autor:
Min, Zhixiang, Dunn, Enrique
We present a dense-indirect SLAM system using external dense optical flows as input. We extend the recent probabilistic visual odometry model VOLDOR [Min et al. CVPR'20], by incorporating the use of geometric priors to 1) robustly bootstrap estimatio
Externí odkaz:
http://arxiv.org/abs/2104.06800
Autor:
Xu, Xiangyu, Dunn, Enrique
We present a general paradigm for dynamic 3D reconstruction from multiple independent and uncontrolled image sources having arbitrary temporal sampling density and distribution. Our graph-theoretic formulation models the Spatio-temporal relationships
Externí odkaz:
http://arxiv.org/abs/1908.11044
We target the problem of sparse 3D reconstruction of dynamic objects observed by multiple unsynchronized video cameras with unknown temporal overlap. To this end, we develop a framework to recover the unknown structure without sequencing information
Externí odkaz:
http://arxiv.org/abs/1605.06863
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