3 citations · 3 across the 10 of their papers we have counts for
11 papers
Dexterity from Supervised Play
Botao He, Yiming Dou, Yiannis Aloimonos +3
How can robots autonomously collect the contact-rich experience needed to learn dexterous manipulation? We present DSP: Dexterity from supervised play, a framework in which a robot…
Cross-Sensor Touch Generation
Samanta Rodriguez, Yiming Dou, Miquel Oller +2
Today's visuo-tactile sensors come in many shapes and sizes, making it challenging to develop general-purpose tactile representations. This is because most models are tied to a spe…
Hearing Hands: Generating Sounds from Physical Interactions in 3D Scenes
Yiming Dou, Wonseok Oh, Yuqing Luo +2
We study the problem of making 3D scene reconstructions interactive by asking the following question: can we predict the sounds of human hands physically interacting with a scene?…
Contrastive Touch-to-Touch Pretraining
Samanta Rodriguez, Yiming Dou, William van den Bogert +4
Today's tactile sensors have a variety of different designs, making it challenging to develop general-purpose methods for processing touch signals. In this paper, we learn a unifie…
Tactile Functasets: Neural Implicit Representations of Tactile Datasets
Sikai Li, Samanta Rodriguez, Yiming Dou +2
Modern incarnations of tactile sensors produce high-dimensional raw sensory feedback such as images, making it challenging to efficiently store, process, and generalize across sens…
Touch2Touch: Cross-Modal Tactile Generation for Object Manipulation
Samanta Rodriguez, Yiming Dou, Miquel Oller +2
Today's touch sensors come in many shapes and sizes. This has made it challenging to develop general-purpose touch processing methods since models are generally tied to one specifi…
Tactile-Augmented Radiance Fields
Yiming Dou, Fengyu Yang, Yi Liu +2
We present a scene representation, which we call a tactile-augmented radiance field (TaRF), that brings vision and touch into a shared 3D space. This representation can be used to…
Binding Touch to Everything: Learning Unified Multimodal Tactile Representations
Fengyu Yang, Chao Feng, Ziyang Chen +8
The ability to associate touch with other modalities has huge implications for humans and computational systems. However, multimodal learning with touch remains challenging due to…
The ObjectFolder Benchmark: Multisensory Learning with Neural and Real Objects
Ruohan Gao, Yiming Dou, Hao Li +5
We introduce the ObjectFolder Benchmark, a benchmark suite of 10 tasks for multisensory object-centric learning, centered around object recognition, reconstruction, and manipulatio…
From Isolated Islands to Pangea: Unifying Semantic Space for Human Action Understanding
Yong-Lu Li, Xiaoqian Wu, Xinpeng Liu +8
Action understanding has attracted long-term attention. It can be formed as the mapping from the physical space to the semantic space. Typically, researchers built datasets accordi…
Discovering A Variety of Objects in Spatio-Temporal Human-Object Interactions
Yong-Lu Li, Hongwei Fan, Zuoyu Qiu +8
Spatio-temporal Human-Object Interaction (ST-HOI) detection aims at detecting HOIs from videos, which is crucial for activity understanding. In daily HOIs, humans often interact wi…