7 papers · 1 filter
LocusGS: Spatially Grounded Tokens for Feed-Forward 3D Gaussian Splatting
Wenyu Li, Sidun Liu, Tongrui Hu +2
Recent query-based feed-forward 3DGS methods represent a scene using learnable queries, each aggregating multi-view evidence and decoding a group of Gaussians. Ideally, different q…
Muskie: Multi-view Masked Image Modeling for 3D Vision Pre-training
Wenyu Li, Sidun Liu, Peng Qiao +2
We present Muskie, a native multi-view vision backbone designed for 3D vision tasks. Unlike existing models, which are frame-wise and exhibit limited multi-view consistency, Muskie…
Mono3R: Exploiting Monocular Cues for Geometric 3D Reconstruction
Wenyu Li, Sidun Liu, Peng Qiao +1
Recent advances in data-driven geometric multi-view 3D reconstruction foundation models (e.g., DUSt3R) have shown remarkable performance across various 3D vision tasks, facilitated…
VoxNeuS: Enhancing Voxel-Based Neural Surface Reconstruction via Gradient Interpolation
Sidun Liu, Peng Qiao, Zongxin Ye +2
Neural Surface Reconstruction learns a Signed Distance Field~(SDF) to reconstruct the 3D model from multi-view images. Previous works adopt voxel-based explicit representation to i…
DistGrid: Scalable Scene Reconstruction with Distributed Multi-resolution Hash Grid
Sidun Liu, Peng Qiao, Zongxin Ye +2
Neural Radiance Field~(NeRF) achieves extremely high quality in object-scaled and indoor scene reconstruction. However, there exist some challenges when reconstructing large-scale…
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey
Marcos V. Conde, Florin-Alexandru Vasluianu, Radu Timofte +32
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in…