WebOptimal and Robust Category-level Perception: Object Pose and Shape Estimation from 2D and 3D Semantic Keypoints Jingnan Shi, Heng Yang, Luca Carlone Fig. 1. We develop algorithms for 3D-3D and 2D-3D category-level perception, which estimate 3D pose and shape of an object from 3D and 2D sensor data, respectively. WebReliable object perception is a vital requirement for automated driving. Despite the availability of precise contour measurements, most state-of-the-art tracking systems still …

Optimal Pose and Shape Estimation for Category-level …

WebMay 8, 2014 · To estimate shape from shading, the visual system biases judgements toward more common scenes, for example, light sources that are roughly overhead ... Experiment 1 demonstrated a clear effect of the presence of a highlight on shape perception – objects with a highlight are more likely to be perceived as convex. The … WebApr 16, 2024 · Optimal Pose and Shape Estimation for Category-level 3D Object Perception. We consider a category-level perception problem, where one is given 3D sensor data picturing an object of a given … how old was asa butterfield in hugo

NVIDIA Learning and Perception Research

WebApr 1, 2024 · Shape estimation is competitive with state-of-the-art methods. probabilistic approach for acquiring object models, based on visual and obtained from two different robots physically interacting with objects. We evaluate performance by assessing how close the reconstructed surfaces are to ground-truth object models. WebPerception for Autonomous Machines: stereo, optical flow, object pose estimation, 3D shape estimation, etc. Neural Content Capture and Synthesis: image and view synthesis, neural avatars, neural agents, denoising diffusion models, GANs, etc. meriden public school logo