90 citations · 678 across the 49 of their papers we have counts for
8 papers · 1 filter
Learnable Spatio-Temporal Map Embeddings for Deep Inertial Localization
Dennis Melamed, Karnik Ram, Vivek Roy +1
Indoor localization systems often fuse inertial odometry with map information via hand-defined methods to reduce odometry drift, but such methods are sensitive to noise and struggl…
3D-Aware Encoding for Style-based Neural Radiance Fields
Yu-Jhe Li, Tao Xu, Bichen Wu +6
We tackle the task of NeRF inversion for style-based neural radiance fields, (e.g., StyleNeRF). In the task, we aim to learn an inversion function to project an input image to the…
Track Targets by Dense Spatio-Temporal Position Encoding
Jinkun Cao, Hao Wu, Kris Kitani
In this work, we propose a novel paradigm to encode the position of targets for target tracking in videos using transformers. The proposed paradigm, Dense Spatio-Temporal (DST) pos…
Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
Jinhyung Park, Chenfeng Xu, Shijia Yang +4
While recent camera-only 3D detection methods leverage multiple timesteps, the limited history they use significantly hampers the extent to which temporal fusion can improve object…
Embodied Scene-aware Human Pose Estimation
Zhengyi Luo, Shun Iwase, Ye Yuan +1
We propose embodied scene-aware human pose estimation where we estimate 3D poses based on a simulated agent's proprioception and scene awareness, along with external third-person o…
Occluded Human Mesh Recovery
Rawal Khirodkar, Shashank Tripathi, Kris Kitani
Top-down methods for monocular human mesh recovery have two stages: (1) detect human bounding boxes; (2) treat each bounding box as an independent single-human mesh recovery task.…
Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking
Jinkun Cao, Jiangmiao Pang, Xinshuo Weng +2
Kalman filter (KF) based methods for multi-object tracking (MOT) make an assumption that objects move linearly. While this assumption is acceptable for very short periods of occlus…
Domain Adaptive Hand Keypoint and Pixel Localization in the Wild
Takehiko Ohkawa, Yu-Jhe Li, Qichen Fu +3
We aim to improve the performance of regressing hand keypoints and segmenting pixel-level hand masks under new imaging conditions (e.g., outdoors) when we only have labeled images…