activity
20242026
most citedEfficient Vision-Language Pre-training by Cluster Masking

2 citations · 3 across the 10 of their papers we have counts for

collaborators

10 papers

cs.RO2026

Unified Motion-Action Modeling for Heterogeneous Robot Learning

Yunhao Cao, Shitong Liu, Chao Feng +4

We present Unified Motion-Action (UMA) Model, an approach that uses 3D object motion trajectories as a shared interface to bridge visuomotor control and dynamics modeling. UMA trea…

cs.RO2025

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…

cs.CV2025

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?…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024

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…

cs.CV2024★ 2 cited

Efficient Vision-Language Pre-training by Cluster Masking

Zihao Wei, Zixuan Pan, Andrew Owens

We propose a simple strategy for masking image patches during visual-language contrastive learning that improves the quality of the learned representations and the training speed.…

cs.CV2024

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…

cs.SD2024★ 1 cited

Real Acoustic Fields: An Audio-Visual Room Acoustics Dataset and Benchmark

Ziyang Chen, Israel D. Gebru, Christian Richardt +4

We present a new dataset called Real Acoustic Fields (RAF) that captures real acoustic room data from multiple modalities. The dataset includes high-quality and densely captured ro…

cs.CV2024

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…