The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

Point cloud registration is a research field where the spatial relationship between two or
more sets of points in space is determined. Point clouds are found in multiple applications …

We introduce PointOdyssey, a large-scale synthetic dataset, and data generation framework,
for the training and evaluation of long-term fine-grained tracking algorithms. Our goal is to …

Implicit neural fields, typically encoded by a multilayer perceptron (MLP) that maps from
coordinates (eg, xyz) to signals (eg, signed distances), have shown remarkable promise as …

The intrinsic rotation invariance lies at the core of matching point clouds with handcrafted
descriptors. However, it is widely despised by recent deep matchers that obtain the rotation …

We introduce Infinigen, a procedural generator of photorealistic 3D scenes of the natural
world. Infinigen is entirely procedural: every asset, from shape to texture, is generated from …

Abstract We present Lepard, a Learning based approach for partial point cloud matching in
rigid and deformable scenes. The key characteristics are the following techniques that …

To make 3D human avatars widely available, we must be able to generate a variety of 3D
virtual humans with varied identities and shapes in arbitrary poses. This task is challenging …

We have recently seen tremendous progress in photo-real human modeling and rendering.
Yet efficiently rendering realistic human performance and integrating it into the rasterization …

We study the problem of extracting accurate correspondences for point cloud registration.
Recent keypoint-free methods have shown great potential through bypassing the detection …