5 citations · 15 across the 41 of their papers we have counts for
16 papers · 1 filter
PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models
Minghao Chen, Roman Shapovalov, Iro Laina +4
Text- or image-to-3D generators and 3D scanners can now produce 3D assets with high-quality shapes and textures. These assets typically consist of a single, fused representation, l…
DualPM: Dual Posed-Canonical Point Maps for 3D Shape and Pose Reconstruction
Ben Kaye, Tomas Jakab, Shangzhe Wu +2
The choice of data representation is a key factor in the success of deep learning in geometric tasks. For instance, DUSt3R recently introduced the concept of viewpoint-invariant po…
MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views
Yuedong Chen, Chuanxia Zheng, Haofei Xu +4
We introduce MVSplat360, a feed-forward approach for 360° novel view synthesis (NVS) of diverse real-world scenes, using only sparse observations. This setting is inherently ill-po…
3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes
Jan Held, Renaud Vandeghen, Abdullah Hamdi +6
Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes wi…
CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos
Nikita Karaev, Iurii Makarov, Jianyuan Wang +3
Most state-of-the-art point trackers are trained on synthetic data due to the difficulty of annotating real videos for this task. However, this can result in suboptimal performance…
Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation
Junlin Han, Jianyuan Wang, Andrea Vedaldi +2
Generating high-quality 3D content from text, single images, or sparse view images remains a challenging task with broad applications. Existing methods typically employ multi-view…
Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics
Ruining Li, Chuanxia Zheng, Christian Rupprecht +1
We introduce Puppet-Master, an interactive video generator that captures the internal, part-level motion of objects, serving as a proxy for modeling object dynamics universally. Gi…
SHIC: Shape-Image Correspondences with no Keypoint Supervision
Aleksandar Shtedritski, Christian Rupprecht, Andrea Vedaldi
Canonical surface mapping generalizes keypoint detection by assigning each pixel of an object to a corresponding point in a 3D template. Popularised by DensePose for the analysis o…
Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Image
Stanislaw Szymanowicz, Eldar Insafutdinov, Chuanxia Zheng +4
We propose Flash3D, a method for scene reconstruction and novel view synthesis from a single image which is both very generalisable and efficient. For generalisability, we start fr…
Lightplane: Highly-Scalable Components for Neural 3D Fields
Ang Cao, Justin Johnson, Andrea Vedaldi +1
Contemporary 3D research, particularly in reconstruction and generation, heavily relies on 2D images for inputs or supervision. However, current designs for these 2D-3D mapping are…
Invisible Stitch: Generating Smooth 3D Scenes with Depth Inpainting
Paul Engstler, Andrea Vedaldi, Iro Laina +1
3D scene generation has quickly become a challenging new research direction, fueled by consistent improvements of 2D generative diffusion models. Most prior work in this area gener…
DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editing
Minghao Chen, Iro Laina, Andrea Vedaldi
We consider the problem of editing 3D objects and scenes based on open-ended language instructions. A common approach to this problem is to use a 2D image generator or editor to gu…
DragAPart: Learning a Part-Level Motion Prior for Articulated Objects
Ruining Li, Chuanxia Zheng, Christian Rupprecht +1
We introduce DragAPart, a method that, given an image and a set of drags as input, generates a new image of the same object that responds to the action of the drags. Differently fr…
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht +4
Most text-to-3D generators build upon off-the-shelf text-to-image models trained on billions of images. They use variants of Score Distillation Sampling (SDS), which is slow, somew…
GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering
Abdullah Hamdi, Luke Melas-Kyriazi, Jinjie Mai +5
Advancements in 3D Gaussian Splatting have significantly accelerated 3D reconstruction and generation. However, it may require a large number of Gaussians, which creates a substant…
Learning the 3D Fauna of the Web
Zizhang Li, Dor Litvak, Ruining Li +6
Learning 3D models of all animals on the Earth requires massively scaling up existing solutions. With this ultimate goal in mind, we develop 3D-Fauna, an approach that learns a pan…