526 citations · 1.4k across the 51 of their papers we have counts for
9 papers · 1 filter
Pose2Room: Understanding 3D Scenes from Human Activities
Yinyu Nie, Angela Dai, Xiaoguang Han +1
With wearable IMU sensors, one can estimate human poses from wearable devices without requiring visual input~\cite{von2017sparse}. In this work, we pose the question: Can we reason…
4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding
Yujin Chen, Matthias Nießner, Angela Dai
We present a new approach to instill 4D dynamic object priors into learned 3D representations by unsupervised pre-training. We observe that dynamic movement of an object through an…
ROCA: Robust CAD Model Retrieval and Alignment from a Single Image
Can Gümeli, Angela Dai, Matthias Nießner
We present ROCA, a novel end-to-end approach that retrieves and aligns 3D CAD models from a shape database to a single input image. This enables 3D perception of an observed scene…
Panoptic 3D Scene Reconstruction From a Single RGB Image
Manuel Dahnert, Ji Hou, Matthias Nießner +1
Understanding 3D scenes from a single image is fundamental to a wide variety of tasks, such as for robotics, motion planning, or augmented reality. Existing works in 3D perception…
Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image
Weicheng Kuo, Anelia Angelova, Tsung-Yi Lin +1
3D perception of object shapes from RGB image input is fundamental towards semantic scene understanding, grounding image-based perception in our spatially 3-dimensional real-world…
TransformerFusion: Monocular RGB Scene Reconstruction using Transformers
Aljaž Božič, Pablo Palafox, Justus Thies +2
We introduce TransformerFusion, a transformer-based 3D scene reconstruction approach. From an input monocular RGB video, the video frames are processed by a transformer network tha…
Pri3D: Can 3D Priors Help 2D Representation Learning?
Ji Hou, Saining Xie, Benjamin Graham +2
Recent advances in 3D perception have shown impressive progress in understanding geometric structures of 3Dshapes and even scenes. Inspired by these advances in geometric understan…
NPMs: Neural Parametric Models for 3D Deformable Shapes
Pablo Palafox, Aljaž Božič, Justus Thies +2
Parametric 3D models have enabled a wide variety of tasks in computer graphics and vision, such as modeling human bodies, faces, and hands. However, the construction of these param…
RetrievalFuse: Neural 3D Scene Reconstruction with a Database
Yawar Siddiqui, Justus Thies, Fangchang Ma +3
3D reconstruction of large scenes is a challenging problem due to the high-complexity nature of the solution space, in particular for generative neural networks. In contrast to tra…