Publication
2025
- ICCVGlobal Motion Corresponder for 3D Point-Based Scene InterpolationJunru Lin*, Chirag Vashist*, Mikaela Angelina Uy, and 4 more authors2025
Existing dynamic scene interpolation methods typically assume that the motion between consecutive timesteps is small enough so that displacements can be locally approximated by linear models. In practice, even slight deviations from this small-motion assumption can cause conventional techniques to fail. In this paper, we introduce Global Motion Corresponder (GMC), a novel approach that robustly handles large motion and achieves smooth transitions. GMC learns unary potential fields that predict SE(3) mappings into a shared canonical space, balancing correspondence, spatial and semantic smoothness, and local rigidity. We demonstrate that our method significantly outperforms existing baselines on 3D scene interpolation when the two states undergo large global motions. Furthermore, our method enables extrapolation capabilities where other baseline methods cannot.
@misc{lin2025gmc, title = {Global Motion Corresponder for 3D Point-Based Scene Interpolation}, author = {Lin*, Junru and Vashist*, Chirag and Uy, Mikaela Angelina and Stearns, Colton and Luo, Xuan and Guibas, Leonidas and Li, Ke}, year = {2025}, }
2024
- IROSTernary-Type Opacity and Hybrid Odometry for RGB NeRF-SLAMJunru Lin, Asen Nachkov, Songyou Peng, and 2 more authorsIn 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2024
In this work, we address the challenge of deploying Neural Radiance Field (NeRFs) in Simultaneous Localization and Mapping (SLAM) under the condition of lacking depth information, relying solely on RGB inputs. The key to unlocking the full potential of NeRF in such a challenging context lies in the integration of real-world priors. A crucial prior we explore is the binary opacity prior of 3D space with opaque objects. To effectively incorporate this prior into the NeRF framework, we introduce a ternary-type opacity (TT) model instead, which categorizes points on a ray intersecting a surface into three regions: before, on, and behind the surface. This enables a more accurate rendering of depth, subsequently improving the performance of image warping techniques. Therefore, we further propose a novel hybrid odometry (HO) scheme that merges bundle adjustment and warping-based localization. Our integrated approach of TT and HO achieves state-of-the-art performance on synthetic and real-world datasets, in terms of both speed and accuracy. This breakthrough underscores the potential of NeRF-SLAM in navigating complex environments with high fidelity.
@inproceedings{lin2023ternarytypeopacityhybridodometry, booktitle = {2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, title = {Ternary-Type Opacity and Hybrid Odometry for RGB NeRF-SLAM}, author = {Lin, Junru and Nachkov, Asen and Peng, Songyou and Gool, Luc Van and Pani Paudel, Danda}, year = {2024}, volume = {}, number = {}, pages = {7929-7936}, keywords = {Location awareness;Solid modeling;Accuracy;Simultaneous localization and mapping;Navigation;Neural radiance field;Rendering (computer graphics);Real-time systems;Odometry;Optimization}, doi = {10.1109/IROS58592.2024.10802493}, }
2022
- SIURORapid Testing in COVID and Modified SIR ModelChen, J.*, Li, R.* and Lin, J.*SIAM Undergraduate Research Online, 2022
The COIVD pandemic has swept the globe since 2019, posing a grave threat to human life. There are multiple ways for the government to control the pandemic, including promoting the vaccination, limiting the number of people in public places, requiring people to wear masks in public places, and suggesting infected people isolate themselves. In this paper, we used a compartmental model to analyze the spread of COVID-19 under the promotion of rapid tests. The result shows that popularization of rapid tests may have a significant impact on controlling the pandemic. With an estimated minimum requirement for the use of rapid tests, we are able to put forward suggestions on reasonable ways to curtail the pandemic.
@article{covid, title = {Rapid Testing in COVID and Modified SIR Model}, author = {{Chen, J.*, Li, R.* and Lin, J.*}}, journal = {SIAM Undergraduate Research Online,}, volume = {15}, year = {2022}, doi = {10.1137/21S1460399}, publisher = {Society for Industrial and Applied Mathematics,}, }