3D Vision

OSDCap: Online optimal-state dynamics estimation selectively incorporates physics models with kinematic observations to achieve highly accurate, physically-plausible human motion capture from videos.

OpenGaussian achieves 3D point-level open vocabulary understanding using 3D Gaussian Splatting by training 3D instance features with high 3D consistency, employing a two-level codebook for feature dis…

OpenDlign uses novel depth-aligned images from a diffusion model to boost open-world 3D understanding, achieving significant performance gains on diverse benchmarks.

OneDet3D: A universal 3D object detector trained jointly on diverse indoor/outdoor datasets, achieving one-for-all performance across domains and categories.

ODGS: Lightning-fast 3D scene reconstruction from single omnidirectional images using 3D Gaussian splatting, achieving 100x speedup over NeRF-based methods.

OctreeOcc uses octree queries for efficient and multi-granularity 3D occupancy prediction, surpassing state-of-the-art methods with reduced computational costs.

OccFusion: High-fidelity human rendering from videos, even with occlusions, using 3D Gaussian splatting and 2D diffusion priors.

Normal-GS improves 3D Gaussian Splatting by integrating normal vectors into the rendering pipeline, achieving near state-of-the-art visual quality with accurate surface normals in real-time.

NeuroGauss4D-PCI masters complex point cloud interpolation using 4D neural fields and Gaussian deformation fields, achieving superior accuracy in dynamic scenes.

NeuRodin: A two-stage neural framework achieves high-fidelity 3D surface reconstruction from posed RGB images by innovatively addressing limitations in SDF-based methods, resulting in superior reconst…

Neural SDF inference is revolutionized by dynamically aligning 3D Gaussians to a neural SDF’s zero-level set, enabling accurate, smooth 3D surface reconstruction.

Learn disentangled 3D object poses and transfer them between different object identities using a novel neural pose representation, boosting 3D shape generation!

Neural Localizer Fields (NLF) revolutionizes 3D human pose and shape estimation by learning a continuous field of point localizer functions, enabling flexible training on diverse data and on-the-fly p…

Neural Isometries learns a latent space where geometric relationships in the observation space are represented as isometries in the latent space, enabling efficient handling of complex symmetries and …

Boosting implicit neural representations, Neural Experts uses a Mixture of Experts architecture to achieve faster, more accurate, and memory-efficient signal reconstruction across various tasks.

NeuMA: a novel neural material adaptor corrects existing physical models, accurately learning complex dynamics from visual observations.

MVSplat360: Generating stunning 360° views from just a few images!

MVSDet uses efficient plane sweeps for accurate indoor 3D object detection from multiple images, significantly outperforming previous NeRF-based methods.

MVInpainter: Pose-free multi-view consistent inpainting bridges 2D and 3D editing by simplifying 3D editing to a multi-view 2D inpainting task.

MVGamba: A unified, feed-forward 3D content generation model achieving state-of-the-art quality and speed using an RNN-like state space model for efficient multi-view Gaussian reconstruction.