12 citations · 21 across the 7 of their papers we have counts for
5 papers · 1 filter
LIDSNet: A Lightweight on-device Intent Detection model using Deep Siamese Network
Vibhav Agarwal, Sudeep Deepak Shivnikar, Sourav Ghosh +2
Intent detection is a crucial task in any Natural Language Understanding (NLU) system and forms the foundation of a task-oriented dialogue system. To build high-quality real-world…
ABO: Dataset and Benchmarks for Real-World 3D Object Understanding
Jasmine Collins, Shubham Goel, Kenan Deng +9
We introduce Amazon Berkeley Objects (ABO), a new large-scale dataset designed to help bridge the gap between real and virtual 3D worlds. ABO contains product catalog images, metad…
RoomStructNet: Learning to Rank Non-Cuboidal Room Layouts From Single View
Xi Zhang, Chun-Kai Wang, Kenan Deng +2
In this paper, we present a new approach to estimate the layout of a room from its single image. While recent approaches for this task use robust features learnt from data, they re…
Multimodal Shape Completion via IMLE
Himanshu Arora, Saurabh Mishra, Shichong Peng +2
Shape completion is the problem of completing partial input shapes such as partial scans. This problem finds important applications in computer vision and robotics due to issues su…
A character representation enhanced on-device Intent Classification
Sudeep Deepak Shivnikar, Himanshu Arora, Harichandana B S S
Intent classification is an important task in natural language understanding systems. Existing approaches have achieved perfect scores on the benchmark datasets. However they are n…