Zobrazeno 1 - 10
of 640
pro vyhledávání: '"Yu, JIngyi"'
The recent popular radiance field models, exemplified by Neural Radiance Fields (NeRF), Instant-NGP and 3D Gaussian Splatting, are designed to represent 3D content by that training models for each individual scene. This unique characteristic of scene
Externí odkaz:
http://arxiv.org/abs/2410.19483
Foundation models in computer vision have demonstrated exceptional performance in zero-shot and few-shot tasks by extracting multi-purpose features from large-scale datasets through self-supervised pre-training methods. However, these models often ov
Externí odkaz:
http://arxiv.org/abs/2410.11373
Motion correction (MoCo) in radial MRI is a challenging problem due to the unpredictability of subject's motion. Current state-of-the-art (SOTA) MoCo algorithms often use extensive high-quality MR images to pre-train neural networks, obtaining excell
Externí odkaz:
http://arxiv.org/abs/2409.16921
Autor:
Wang, Penghao, Zhang, Zhirui, Wang, Liao, Yao, Kaixin, Xie, Siyuan, Yu, Jingyi, Wu, Minye, Xu, Lan
Experiencing high-fidelity volumetric video as seamlessly as 2D videos is a long-held dream. However, current dynamic 3DGS methods, despite their high rendering quality, face challenges in streaming on mobile devices due to computational and bandwidt
Externí odkaz:
http://arxiv.org/abs/2409.13648
Autor:
Jiang, Yuheng, Shen, Zhehao, Hong, Yu, Guo, Chengcheng, Wu, Yize, Zhang, Yingliang, Yu, Jingyi, Xu, Lan
Volumetric video represents a transformative advancement in visual media, enabling users to freely navigate immersive virtual experiences and narrowing the gap between digital and real worlds. However, the need for extensive manual intervention to st
Externí odkaz:
http://arxiv.org/abs/2409.08353
Autor:
Qin, Dafei, Lin, Hongyang, Zhang, Qixuan, Qiao, Kaichun, Zhang, Longwen, Zhao, Zijun, Saito, Jun, Yu, Jingyi, Xu, Lan, Komura, Taku
We propose GauFace, a novel Gaussian Splatting representation, tailored for efficient animation and rendering of physically-based facial assets. Leveraging strong geometric priors and constrained optimization, GauFace ensures a neat and structured Ga
Externí odkaz:
http://arxiv.org/abs/2409.07441
Autor:
Yao, Bowei, Cui, Shilong, Dai, Haizhao, Wu, Qing, Xiao, Youshen, Gao, Fei, Yu, Jingyi, Zhang, Yuyao, Cai, Xiran
High-quality imaging in photoacoustic computed tomography (PACT) usually requires a high-channel count system for dense spatial sampling around the object to avoid aliasing-related artefacts. To reduce system complexity, various image reconstruction
Externí odkaz:
http://arxiv.org/abs/2409.13696
Sign languages, used by around 70 million Deaf individuals globally, are visual languages that convey visual and contextual information. Current methods in vision-based sign language recognition (SLR) and translation (SLT) struggle with dialogue scen
Externí odkaz:
http://arxiv.org/abs/2409.01073
Modeling and capturing the 3D spatial arrangement of the human and the object is the key to perceiving 3D human-object interaction from monocular images. In this work, we propose to use the Human-Object Offset between anchors which are densely sample
Externí odkaz:
http://arxiv.org/abs/2407.20545
Autor:
Yao, Bowei, Zeng, Yi, Dai, Haizhao, Wu, Qing, Xiao, Youshen, Gao, Fei, Zhang, Yuyao, Yu, Jingyi, Cai, Xiran
Photoacoustic tomography is a hybrid biomedical technology, which combines the advantages of acoustic and optical imaging. However, for the conventional image reconstruction method, the image quality is affected obviously by artifacts under the condi
Externí odkaz:
http://arxiv.org/abs/2406.17578