ΑΙhub.org
Making sense of vision and touch: #ICRA2019 best paper award video and interview
PhD candidate Michelle A. Lee from the Stanford AI Lab won the best paper award at ICRA 2019 with her work “Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks”. You can read the paper on arxiv here.
Audrow Nash was there to capture her pitch.
And here’s the official video about the work.
Full reference
Lee, Michelle A., Yuke Zhu, Krishnan Srinivasan, Parth Shah, Silvio Savarese, Li Fei-Fei, Animesh Garg, and Jeannette Bohg. “Making sense of vision and touch: Self-supervised learning of multimodal representations for contact-rich tasks.” arXiv preprint arXiv:1810.10191 (2018).
AIhub
is dedicated to free high-quality information about AI.
AIhub
is dedicated to free high-quality information about AI.
AIhub is supported by:
Related posts :
Generative AI is already being used in journalism – here’s how people feel about it
The Conversation
21 Feb 2025
New report draws on three years of interviews and focus group research into generative AI and journalism
Charlotte Bunne on developing AI-based diagnostic tools
EPFL
20 Feb 2025
To advance modern medicine, EPFL researchers are developing AI-based diagnostic tools. Their goal is to predict the best treatment a patient should receive.
What’s coming up at #AAAI2025?
Lucy Smith
19 Feb 2025
Find out what's on the programme at the 39th Annual AAAI Conference on Artificial Intelligence
An introduction to science communication at #AAAI2025
Lucy Smith
18 Feb 2025
Find out more about our forthcoming training session at AAAI on 26 February 2025.
The Good Robot podcast: Critiquing tech through comedy with Laura Allcorn
The Good Robot Podcast
17 Feb 2025
Eleanor and Kerry chat to Laura Allcorn about how she pairs humour and entertainment with participatory public engagement to raise awareness of AI use cases
Interview with Kayla Boggess: Explainable AI for more accessible and understandable technologies
Lucy Smith
14 Feb 2025
Hear from Doctoral Consortium participant Kayla about her work focussed on explanations for multi-agent reinforcement learning, and human-centric explanations.
The Machine Ethics podcast: Running faster with Enrico Panai
The Machine Ethics Podcast
13 Feb 2025
This episode, Ben chats to Enrico Panai about different aspects of AI ethics.
Diffusion model predicts 3D genomic structures
MIT News
12 Feb 2025
A new approach predicts how a specific DNA sequence will arrange itself in the cell nucleus.