1 code implementation • 22 Jan 2024 • Chenjie Cao, Xinlin Ren, Yanwei Fu
Recent advancements in learning-based Multi-View Stereo (MVS) methods have prominently featured transformer-based models with attention mechanisms.
Ranked #1 on Point Clouds on Tanks and Temples
no code implementations • 11 Mar 2023 • Chenjie Cao, Xinlin Ren, xiangyang xue, Yanwei Fu
To address these problems, we first apply one of the state-of-the-art learning-based MVS methods, --MVSFormer, to overcome intractable scenarios such as textureless and reflections regions suffered by traditional PatchMatch methods, but it fails in a few large scenes' reconstructions.
1 code implementation • 18 Aug 2022 • Boyan Jiang, Xinlin Ren, Mingsong Dou, xiangyang xue, Yanwei Fu, yinda zhang
Recent progress in 4D implicit representation focuses on globally controlling the shape and motion with low dimensional latent vectors, which is prone to missing surface details and accumulating tracking error.
1 code implementation • 4 Aug 2022 • Chenjie Cao, Xinlin Ren, Yanwei Fu
In this paper, we propose a pre-trained ViT enhanced MVS network called MVSFormer, which can learn more reliable feature representations benefited by informative priors from ViT.
Ranked #2 on 3D Reconstruction on DTU
no code implementations • CVPR 2022 • Yun He, Xinlin Ren, Danhang Tang, yinda zhang, xiangyang xue, Yanwei Fu
To address this, we propose a novel deep point cloud compression method that preserves local density information.