3D Vision

Sara Rojas
Ali Thabet
Bernard Ghanem
Pablo Arbeláez

Encouraged by evolving research fields such as Artificial Reality, Autonomous vehicles, and scene understanding, 3D Vision problems have gained interest recently. Many of the tasks studied in 3D Vision are inspired by its 2D counterpart. However, the extending of deep learning into depth and 3D information can unlock a variety of applications. Contrary to 2D Vision problems that study 2D standard-images, 3D data is structured in different formats, including RGB-D images, voxel grids, point clouds, and meshes. This diversity and the need for low-computational-cost processing is a challenge for research in this area.

Point-cloud Analysis

AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds

A. Hamdi, S. Rojas, A. Thabet and B. Ghanem


Human Pose Estimation

Precise human pose estimation based on two-dimensional images for kinematic analysis

S. Rojas, D. Herrera, P. Arbeláez

International Symposium on Medical Information Processing and Analysis (SIPAIM), 2019

Articulated Pose Estimation using Discriminative Armlet Classifiers

G. Gkioxari, P. Arbelaez, L. Bourdev and J. Malik

CVPR, 2013

RGB-D Analysis

Aligning 3D Models to RGB-D Images of Cluttered Scenes

S. Gupta, P. Arbelaez, R. Girshick and J. Malik

CVPR, 2015

Indoor Scene Understanding with RGB-D Images: Bottom-up Segmentation, Object Detection and Semantic Segmentation

S. Gupta, P. Arbelaez, R. Girshick and J. Malik

International Journal of Computer Vision (IJCV), 2015

Learning Rich Features from RGB-D Images for Object Detection and Segmentation

S. Gupta, R.Girshick, P. Arbelaez and J. Malik

ECCV, 2014

Perceptual Organization and Recognition of Indoor Scenes from RGBD Images

S. Gupta, P. Arbelaez and J. Malik

CVPR, 2013. (oral)

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