Metric learning aims to measure the similarity among samples while using an optimal
distance metric for learning tasks. Metric learning methods, which generally use a linear …

Deep learning has recently gained popularity achieving state-of-the-art performance in tasks
involving text, sound, or image processing. Due to its outstanding performance, there have …

Retrieving 3D models from 2D human sketches has received considerable attention in the
areas of graphics, image retrieval, and computer vision. Almost always in state of the art …

Free-hand sketches are highly illustrative, and have been widely used by humans to depict
objects or stories from ancient times to the present. The recent prevalence of touchscreen …

Sketching is a powerful tool for creating abstract images that are sparse but meaningful.
Sketch understanding poses fundamental challenges for general-purpose vision algorithms …

Large-scale 3D shape retrieval has become an important research direction in content-
based 3D shape retrieval. To promote this research area, two Shape Retrieval Contest …

Large scale sketch-based 3D shape retrieval has received more and more attentions in the
community of contentbased 3D object retrieval. The objective of this track is to evaluate the …

In this paper we study, for the first time, the problem of fine-grained sketch-based 3D shape
retrieval. We advocate the use of sketches as a fine-grained input modality to retrieve 3D …

Retrieving 3D shapes with sketches is a challenging problem since 2D sketches and 3D
shapes are from two heterogeneous domains, which results in large discrepancy between …

Diffusion process has advanced object retrieval greatly as it can capture the underlying
manifold structure. Recent studies have experimentally demonstrated that tensor product …