5 citations · 15 across the 41 of their papers we have counts for
16 papers · 2 filters
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…