9 citations · 24 across the 7 of their papers we have counts for
7 papers
CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding
Chenyang Ma, Kai Lu, Guangyu Yang +6
Current work on robot failure detection and correction typically operates in a post hoc manner, analyzing errors and applying corrections only after failures occur. This work intro…
When the Sun Goes Down: Repairing Photometric Losses for All-Day Depth Estimation
Madhu Vankadari, Stuart Golodetz, Sourav Garg +3
Self-supervised deep learning methods for joint depth and ego-motion estimation can yield accurate trajectories without needing ground-truth training data. However, as they typical…
OdomBeyondVision: An Indoor Multi-modal Multi-platform Odometry Dataset Beyond the Visible Spectrum
Peize Li, Kaiwen Cai, Muhamad Risqi U. Saputra +4
This paper presents a multimodal indoor odometry dataset, OdomBeyondVision, featuring multiple sensors across the different spectrum and collected with different mobile platforms.…
RangeUDF: Semantic Surface Reconstruction from 3D Point Clouds
Bing Wang, Zhengdi Yu, Bo Yang +5
We present RangeUDF, a new implicit representation based framework to recover the geometry and semantics of continuous 3D scene surfaces from point clouds. Unlike occupancy fields…
Graph-based Thermal-Inertial SLAM with Probabilistic Neural Networks
Muhamad Risqi U. Saputra, Chris Xiaoxuan Lu, Pedro P. B. de Gusmao +3
Simultaneous Localization and Mapping (SLAM) system typically employ vision-based sensors to observe the surrounding environment. However, the performance of such systems highly de…
VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization
Kaichen Zhou, Changhao Chen, Bing Wang +3
Recent learning-based approaches have achieved impressive results in the field of single-shot camera localization. However, how best to fuse multiple modalities (e.g., image and de…
DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction
Changhao Chen, Chris Xiaoxuan Lu, Bing Wang +2
Dynamical models estimate and predict the temporal evolution of physical systems. State Space Models (SSMs) in particular represent the system dynamics with many desirable properti…