266 citations · 981 across the 59 of their papers we have counts for
8 papers · 1 filter
Transductive Zero-Shot Learning for 3D Point Cloud Classification
Ali Cheraghian, Shafin Rahman, Dylan Campbell +1
Zero-shot learning, the task of learning to recognize new classes not seen during training, has received considerable attention in the case of 2D image classification. However desp…
Contextually Plausible and Diverse 3D Human Motion Prediction
Sadegh Aliakbarian, Fatemeh Sadat Saleh, Lars Petersson +2
We tackle the task of diverse 3D human motion prediction, that is, forecasting multiple plausible future 3D poses given a sequence of observed 3D poses. In this context, a popular…
CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose Estimation
Kartik Gupta, Lars Petersson, Richard Hartley
We present a new approach for a single view, image-based object pose estimation. Specifically, the problem of culling false positives among several pose proposal estimates is addre…
Super-resolved Chromatic Mapping of Snapshot Mosaic Image Sensors via a Texture Sensitive Residual Network
Mehrdad Shoeiby, Lars Petersson, Mohammad Ali Armin +2
This paper introduces a novel method to simultaneously super-resolve and colour-predict images acquired by snapshot mosaic sensors. These sensors allow for spectral images to be ac…
Multi-FAN: Multi-Spectral Mosaic Super-Resolution Via Multi-Scale Feature Aggregation Network
Mehrdad Shoeiby, Sadegh Aliakbarian, Saeed Anwar +1
This paper introduces a novel method to super-resolve multi-spectral images captured by modern real-time single-shot mosaic image sensors, also known as multi-spectral cameras. Our…
Learning Variations in Human Motion via Mix-and-Match Perturbation
Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann +3
Human motion prediction is a stochastic process: Given an observed sequence of poses, multiple future motions are plausible. Existing approaches to modeling this stochasticity typi…
Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects
Ali Cheraghian, Shafin Rahman, Dylan Campbell +1
The development of advanced 3D sensors has enabled many objects to be captured in the wild at a large scale, and a 3D object recognition system may therefore encounter many objects…
Zero-shot Learning of 3D Point Cloud Objects
Ali Cheraghian, Shafin Rahman, Lars Petersson
Recent deep learning architectures can recognize instances of 3D point cloud objects of previously seen classes quite well. At the same time, current 3D depth camera technology all…