activity
20172022
most citedDublinCity: Annotated LiDAR Point Cloud and its Applications

50 citations · 122 across the 17 of their papers we have counts for

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13 papers · 1 filter

cs.CV2022★ 5 cited

KinePose: A temporally optimized inverse kinematics technique for 6DOF human pose estimation with biomechanical constraints

Kevin Gildea, Clara Mercadal-Baudart, Richard Blythman +2

Computer vision/deep learning-based 3D human pose estimation methods aim to localize human joints from images and videos. Pose representation is normally limited to 3D joint positi…

cs.CV2021★ 4 cited

TEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding

Zhengwei Wang, Qi She, Aljosa Smolic

Most of existing video action recognition models ingest raw RGB frames. However, the raw video stream requires enormous storage and contains significant temporal redundancy. Video…

cs.CV2021★ 2 cited

Spectral analysis of re-parameterized light fields

Martin Alain, Aljosa Smolic

In this paper, we study the spectral properties of re-parameterized light field. Following previous studies of the light field spectrum, which notably provided sampling guidelines,…

cs.CV2021

Foreground color prediction through inverse compositing

Sebastian Lutz, Aljosa Smolic

In natural image matting, the goal is to estimate the opacity of the foreground object in the image. This opacity controls the way the foreground and background is blended in trans…

cs.CV2021

DuctTake: Spatiotemporal Video Compositing

Jan Rueegg, Oliver Wang, Aljoscha Smolic +1

DuctTake is a system designed to enable practical compositing of multiple takes of a scene into a single video. Current industry solutions are based around object segmentation, a h…

cs.CV2020★ 2 cited

CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition

Zhengwei Wang, Qi She, Tejo Chalasani +1

Egocentric gestures are the most natural form of communication for humans to interact with wearable devices such as VR/AR helmets and glasses. A major issue in such scenarios for r…

cs.CV2019

Simultaneous Segmentation and Recognition: Towards more accurate Ego Gesture Recognition

Tejo Chalasani, Aljosa Smolic

Ego hand gestures can be used as an interface in AR and VR environments. While the context of an image is important for tasks like scene understanding, object recognition, image ca…

cs.CV2019★ 50 cited

DublinCity: Annotated LiDAR Point Cloud and its Applications

S. M. Iman Zolanvari, Susana Ruano, Aakanksha Rana +4

Scene understanding of full-scale 3D models of an urban area remains a challenging task. While advanced computer vision techniques offer cost-effective approaches to analyse 3D urb…

cs.CV2018★ 1 cited

Dynamic Environment Mapping for Augmented Reality Applications on Mobile Devices

Rafael Monroy, Matis Hudon, Aljosa Smolic

Augmented Reality is a topic of foremost interest nowadays. Its main goal is to seamlessly blend virtual content in real-world scenes. Due to the lack of computational power in mob…

cs.CV2018

A Pipeline for Lenslet Light Field Quality Enhancement

Pierre Matysiak, Mairéad Grogan, Mikaël Le Pendu +2

In recent years, light fields have become a major research topic and their applications span across the entire spectrum of classical image processing. Among the different methods u…

cs.CV2018

Egocentric Gesture Recognition for Head-Mounted AR devices

Tejo Chalasani, Jan Ondrej, Aljosa Smolic

Natural interaction with virtual objects in AR/VR environments makes for a smooth user experience. Gestures are a natural extension from real world to augmented space to achieve th…

cs.CV2018★ 28 cited

AlphaGAN: Generative adversarial networks for natural image matting

Sebastian Lutz, Konstantinos Amplianitis, Aljosa Smolic

We present the first generative adversarial network (GAN) for natural image matting. Our novel generator network is trained to predict visually appealing alphas with the addition o…

cs.CV2017

SalNet360: Saliency Maps for omni-directional images with CNN

Rafael Monroy, Sebastian Lutz, Tejo Chalasani +1

The prediction of Visual Attention data from any kind of media is of valuable use to content creators and used to efficiently drive encoding algorithms. With the current trend in t…