  The retrieval of 3D objects has gained significant importance in recent years
due to its broad range of applications in computer vision, computer graphics,
virtual reality, and augmented reality. However, the retrieval of 3D objects
presents significant challenges due to the intricate nature of 3D models, which
can vary in shape, size, and texture, and have numerous polygons and vertices.
To this end, we introduce a novel SHREC challenge track that focuses on
retrieving relevant 3D animal models from a dataset using sketch queries and
expedites accessing 3D models through available sketches. Furthermore, a new
dataset named ANIMAR was constructed in this study, comprising a collection of
711 unique 3D animal models and 140 corresponding sketch queries. Our contest
requires participants to retrieve 3D models based on complex and detailed
sketches. We receive satisfactory results from eight teams and 204 runs.
Although further improvement is necessary, the proposed task has the potential
to incentivize additional research in the domain of 3D object retrieval,
potentially yielding benefits for a wide range of applications. We also provide
insights into potential areas of future research, such as improving techniques
for feature extraction and matching and creating more diverse datasets to
evaluate retrieval performance. https://aichallenge.hcmus.edu.vn/sketchanimar
