1 code implementation • 17 Oct 2017 • Li Yi, Lin Shao, Manolis Savva, Haibin Huang, Yang Zhou, Qirui Wang, Benjamin Graham, Martin Engelcke, Roman Klokov, Victor Lempitsky, Yuan Gan, Pengyu Wang, Kun Liu, Fenggen Yu, Panpan Shui, Bingyang Hu, Yan Zhang, Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Minki Jeong, Jaehoon Choi, Changick Kim, Angom Geetchandra, Narasimha Murthy, Bhargava Ramu, Bharadwaj Manda, M. Ramanathan, Gautam Kumar, P Preetham, Siddharth Srivastava, Swati Bhugra, Brejesh lall, Christian Haene, Shubham Tulsiani, Jitendra Malik, Jared Lafer, Ramsey Jones, Siyuan Li, Jie Lu, Shi Jin, Jingyi Yu, Qi-Xing Huang, Evangelos Kalogerakis, Silvio Savarese, Pat Hanrahan, Thomas Funkhouser, Hao Su, Leonidas Guibas
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database.
1 code implementation • 13 Jul 2021 • Bharadwaj Manda, Shubham Dhayarkar, Sai Mitheran, V. K. Viekash, Ramanathan Muthuganapathy
Using the sketch images from this dataset, the paper also aims at evaluating the performance of various retrieval system or a search engine for 3D CAD models that accepts a sketch image as the input query.
1 code implementation • 14 Jul 2021 • Bharadwaj Manda, Pranjal Bhaskare, Ramanathan Muthuganapathy
using deep networks as well as other network architectures on the CADNET.
no code implementations • 2 Jul 2022 • Bharadwaj Manda, Prasad Kendre, Subhrajit Dey, Ramanathan Muthuganapathy
This network takes the defective query sketch as the input and generates a clean or an enhanced query sketch.