8 citations · 19 across the 19 of their papers we have counts for
6 papers · 1 filter
M4Human: A Large-Scale Multimodal mmWave Radar Benchmark for Human Mesh Reconstruction
Junqiao Fan, Yunjiao Zhou, Yizhuo Yang +6
Human mesh reconstruction (HMR) provides direct insights into body-environment interaction, which enables various immersive applications. While existing large-scale HMR datasets re…
Attentive Feature Aggregation or: How Policies Learn to Stop Worrying about Robustness and Attend to Task-Relevant Visual Cues
Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +4
The adoption of pre-trained visual representations (PVRs), leveraging features from large-scale vision models, has become a popular paradigm for training visuomotor policies. Howev…
InverTwin: Solving Inverse Problems via Differentiable Radio Frequency Digital Twin
Xingyu Chen, Jianrong Ding, Kai Zheng +4
Digital twins (DTs), virtual simulated replicas of physical scenes, are transforming various industries. However, their potential in radio frequency (RF) sensing applications has b…
VISC: mmWave Radar Scene Flow Estimation using Pervasive Visual-Inertial Supervision
Kezhong Liu, Yiwen Zhou, Mozi Chen +5
This work proposes a mmWave radar's scene flow estimation framework supervised by data from a widespread visual-inertial (VI) sensor suite, allowing crowdsourced training data from…
Fast ECoT: Efficient Embodied Chain-of-Thought via Thoughts Reuse
Zhekai Duan, Yuan Zhang, Shikai Geng +3
Embodied Chain-of-Thought (ECoT) reasoning enhances vision-language-action (VLA) models by improving performance and interpretability through intermediate reasoning steps. However,…
The Temporal Trap: Entanglement in Pre-Trained Visual Representations for Visuomotor Policy Learning
Nikolaos Tsagkas, Andreas Sochopoulos, Duolikun Danier +2
The integration of pre-trained visual representations (PVRs) has significantly advanced visuomotor policy learning. However, effectively leveraging these models remains a challenge…