LaserFlow: Efficient and Probabilistic Object Detection and Motion Forecasting
نویسندگان
چکیده
In this work, we present LaserFlow, an efficient method for 3D object detection and motion forecasting from LiDAR. Unlike the previous our approach utilizes native range view representation of LiDAR, which enables to operate at full sensor in real-time without voxelization or compression data. We propose a new multi-sweep fusion architecture, extracts merges temporal features directly images. Furthermore, novel technique learning probability distribution over future trajectories inspired by curriculum learning. evaluate LaserFlow on two autonomous driving datasets demonstrate competitive results when compared existing state-of-the-art methods.
منابع مشابه
Probabilistic Detection and Tracking of Motion Discontinuities
We propose a Bayesian framework for representing and recognizing local image motion in terms of two primitive models: translation and motion discontinuity. Motion discontinuities are represented using a non-linear generative model that explicitly encodes the orientation of the boundary, the velocities on either side, the motion of the occluding edge over time, and the appearance/disappearance o...
متن کاملAn Efficient Moving Object Detection and Description
In this paper, a new algorithm of moving objects detection and description is proposed. Based on the analysis of projection of the 3D motion of objects, the information of motion field is exploited to make moving object detection more efficient. The discontinuities of motion vector field on the boundaries of moving objects enable us to detect the moving objects blocks in which the potential bou...
متن کاملinvestigation of single-user and multi-user detection methods in mc-cdma systems and comparison of their performances
در این پایان نامه به بررسی روش های آشکارسازی در سیستم های mc-cdma می پردازیم. با توجه به ماهیت آشکارسازی در این سیستم ها، تکنیک های آشکارسازی را می توان به دو دسته ی اصلی تقسیم نمود: آشکارسازی سیگنال ارسالی یک کاربر مطلوب بدون در نظر گرفتن اطلاعاتی در مورد سایر کاربران تداخل کننده که از آن ها به عنوان آشکارساز های تک کاربره یاد می شود و همچنین آشکارسازی سیگنال ارسالی همه ی کاربران فعال موجود در...
Probabilistic visual learning for object detection
We present an unsupervised technique for visual learning which is based on density estimation in high-dimensional spaces using an eigenspace decomposition. Two types of density estimates are derived for modeling the training data: a multivariate Gaussian (for a unimodal distribution) and a multivariate Mixture-of-Gaussians model (for multimodal distributions). These probability densities are th...
متن کاملObject Detection Using Probabilistic Graph Model
We propose a Probabilistic Graph based Model for interactive image segmentation. A multilayer probabilistic Graph is constructed from an oversegmentation of the image to model the relationships among super pixel regions, edge segments and vertices. We used an iterative procedure to merge several regions based on the probability of the regions. Regions are merged until the user is satisfied with...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE robotics and automation letters
سال: 2021
ISSN: ['2377-3766']
DOI: https://doi.org/10.1109/lra.2020.3047793