8 papers
GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels
Dylan Turpin, Liquan Wang, Stavros Tsogkas +2
Tool use requires reasoning about the fit between an object's affordances and the demands of a task. Visual affordance learning can benefit from goal-directed interaction experienc…
Learning Compositional Shape Priors for Few-Shot 3D Reconstruction
Mateusz Michalkiewicz, Stavros Tsogkas, Sarah Parisot +3
The impressive performance of deep convolutional neural networks in single-view 3D reconstruction suggests that these models perform non-trivial reasoning about the 3D structure of…
Cycle-Consistent Generative Rendering for 2D-3D Modality Translation
Tristan Aumentado-Armstrong, Alex Levinshtein, Stavros Tsogkas +2
For humans, visual understanding is inherently generative: given a 3D shape, we can postulate how it would look in the world; given a 2D image, we can infer the 3D structure that l…
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
Kai Zhang, Martin Danelljan, Yawei Li +75
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an in…
Few-Shot Single-View 3-D Object Reconstruction with Compositional Priors
Mateusz Michalkiewicz, Sarah Parisot, Stavros Tsogkas +3
The impressive performance of deep convolutional neural networks in single-view 3D reconstruction suggests that these models perform non-trivial reasoning about the 3D structure of…
Appearance Shock Grammar for Fast Medial Axis Extraction from Real Images
Charles-Olivier Dufresne Camaro, Morteza Rezanejad, Stavros Tsogkas +2
We combine ideas from shock graph theory with more recent appearance-based methods for medial axis extraction from complex natural scenes, improving upon the present best unsupervi…