2 citations · 2 across the 7 of their papers we have counts for
9 papers
TartanMatch: Towards Universal Dense Correspondence Across Modalities
Hyeokjoon Kwon, Jiting Cai, Ruogu Li +7
Robotic platforms combine multi-modal sensors to operate across diverse conditions, but most dense correspondence methods are limited to RGB-RGB or a small set of modality pairs. T…
MAC-I: Learned Metrics-Aware Covariance for Robust Visual-Inertial Fusion in Initialization and Calibration
Xiang Fei, Yuheng Qiu, Can Xu +5
Visual-Inertial (VI) fusion is fundamental to accurate and robust state estimation, where camera and IMU measurements are combined according to their respective uncertainties. Exis…
RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models
Omar Alama, Darshil Jariwala, Avigyan Bhattacharya +3
Open-vocabulary semantic segmentation (OVSS) underpins many vision and robotics tasks that require generalizable semantic understanding. Existing approaches either rely on limited…
RAVEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation
Seungchan Kim, Omar Alama, Dmytro Kurdydyk +5
Aerial outdoor semantic navigation requires robots to explore large, unstructured environments to locate target objects. Recent advances in semantic navigation have demonstrated op…
UFM: A Simple Path towards Unified Dense Correspondence with Flow
Yuchen Zhang, Nikhil Keetha, Chenwei Lyu +9
Dense image correspondence is central to many applications, such as visual odometry, 3D reconstruction, object association, and re-identification. Historically, dense correspondenc…
TartanGround: A Large-Scale Dataset for Ground Robot Perception and Navigation
Manthan Patel, Fan Yang, Yuheng Qiu +4
We present TartanGround, a large-scale, multi-modal dataset to advance the perception and autonomy of ground robots operating in diverse environments. This dataset, collected in va…
RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration
Omar Alama, Avigyan Bhattacharya, Haoyang He +6
Open-set semantic mapping is crucial for open-world robots. Current mapping approaches either are limited by the depth range or only map beyond-range entities in constrained settin…
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation
Bowen Li, Zhaoyu Li, Qiwei Du +10
Recent years have witnessed the rapid development of Neuro-Symbolic (NeSy) AI systems, which integrate symbolic reasoning into deep neural networks. However, most of the existing b…
MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry
Yuheng Qiu, Yutian Chen, Zihao Zhang +2
We propose the MAC-VO, a novel learning-based stereo VO that leverages the learned metrics-aware matching uncertainty for dual purposes: selecting keypoint and weighing the residua…