SketchANIMAR: Sketch-based 3D Animal Fine-Grained Retrieval
Abstract
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
Cite
@article{arxiv.2304.05731,
title = {SketchANIMAR: Sketch-based 3D Animal Fine-Grained Retrieval},
author = {Trung-Nghia Le and Tam V. Nguyen and Minh-Quan Le and Trong-Thuan Nguyen and Viet-Tham Huynh and Trong-Le Do and Khanh-Duy Le and Mai-Khiem Tran and Nhat Hoang-Xuan and Thang-Long Nguyen-Ho and Vinh-Tiep Nguyen and Nhat-Quynh Le-Pham and Huu-Phuc Pham and Trong-Vu Hoang and Quang-Binh Nguyen and Trong-Hieu Nguyen-Mau and Tuan-Luc Huynh and Thanh-Danh Le and Ngoc-Linh Nguyen-Ha and Tuong-Vy Truong-Thuy and Truong Hoai Phong and Tuong-Nghiem Diep and Khanh-Duy Ho and Xuan-Hieu Nguyen and Thien-Phuc Tran and Tuan-Anh Yang and Kim-Phat Tran and Nhu-Vinh Hoang and Minh-Quang Nguyen and Hoai-Danh Vo and Minh-Hoa Doan and Hai-Dang Nguyen and Akihiro Sugimoto and Minh-Triet Tran},
journal= {arXiv preprint arXiv:2304.05731},
year = {2023}
}
Comments
Accepted to Computers & Graphics (3DOR 2023, Journal track)