114 citations · 183 across the 20 of their papers we have counts for
19 papers · 1 filter
PPEA-Depth: Progressive Parameter-Efficient Adaptation for Self-Supervised Monocular Depth Estimation
Yue-Jiang Dong, Yuan-Chen Guo, Ying-Tian Liu +2
Self-supervised monocular depth estimation is of significant importance with applications spanning across autonomous driving and robotics. However, the reliance on self-supervision…
Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers
Zi-Xin Zou, Zhipeng Yu, Yuan-Chen Guo +4
Recent advancements in 3D reconstruction from single images have been driven by the evolution of generative models. Prominent among these are methods based on Score Distillation Sa…
PI3D: Efficient Text-to-3D Generation with Pseudo-Image Diffusion
Ying-Tian Liu, Yuan-Chen Guo, Guan Luo +3
Diffusion models trained on large-scale text-image datasets have demonstrated a strong capability of controllable high-quality image generation from arbitrary text prompts. However…
DreamComposer: Controllable 3D Object Generation via Multi-View Conditions
Yunhan Yang, Yukun Huang, Xiaoyang Wu +5
Utilizing pre-trained 2D large-scale generative models, recent works are capable of generating high-quality novel views from a single in-the-wild image. However, due to the lack of…
Wonder3D: Single Image to 3D using Cross-Domain Diffusion
Xiaoxiao Long, Yuan-Chen Guo, Cheng Lin +8
In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images.Recent methods based on Score Distillation Samp…
Text-to-3D with Classifier Score Distillation
Xin Yu, Yuan-Chen Guo, Yangguang Li +3
Text-to-3D generation has made remarkable progress recently, particularly with methods based on Score Distillation Sampling (SDS) that leverages pre-trained 2D diffusion models. Wh…
PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas
Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo +3
Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (V…
DualVector: Unsupervised Vector Font Synthesis with Dual-Part Representation
Ying-Tian Liu, Zhifei Zhang, Yuan-Chen Guo +3
Automatic generation of fonts can be an important aid to typeface design. Many current approaches regard glyphs as pixelated images, which present artifacts when scaling and inevit…
VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthesis
Yuan-Chen Guo, Yan-Pei Cao, Chen Wang +4
With the emergence of neural radiance fields (NeRFs), view synthesis quality has reached an unprecedented level. Compared to traditional mesh-based assets, this volumetric represen…
MBPTrack: Improving 3D Point Cloud Tracking with Memory Networks and Box Priors
Tian-Xing Xu, Yuan-Chen Guo, Yu-Kun Lai +1
3D single object tracking has been a crucial problem for decades with numerous applications such as autonomous driving. Despite its wide-ranging use, this task remains challenging…
CXTrack: Improving 3D Point Cloud Tracking with Contextual Information
Tian-Xing Xu, Yuan-Chen Guo, Yu-Kun Lai +1
3D single object tracking plays an essential role in many applications, such as autonomous driving. It remains a challenging problem due to the large appearance variation and the s…
StructNeRF: Neural Radiance Fields for Indoor Scenes with Structural Hints
Zheng Chen, Chen Wang, Yuan-Chen Guo +1
Neural Radiance Fields (NeRF) achieve photo-realistic view synthesis with densely captured input images. However, the geometry of NeRF is extremely under-constrained given sparse v…
Gradient-based Point Cloud Denoising with Uniformity
Tian-Xing Xu, Yuan-Chen Guo, Yong-Liang Yang +1
Point clouds captured by depth sensors are often contaminated by noises, obstructing further analysis and applications. In this paper, we emphasize the importance of point distribu…
NeRF-SR: High-Quality Neural Radiance Fields using Supersampling
Chen Wang, Xian Wu, Yuan-Chen Guo +3
We present NeRF-SR, a solution for high-resolution (HR) novel view synthesis with mostly low-resolution (LR) inputs. Our method is built upon Neural Radiance Fields (NeRF) that pre…
NeRFReN: Neural Radiance Fields with Reflections
Yuan-Chen Guo, Di Kang, Linchao Bao +2
Neural Radiance Fields (NeRF) has achieved unprecedented view synthesis quality using coordinate-based neural scene representations. However, NeRF's view dependency can only handle…
Deep Image Synthesis from Intuitive User Input: A Review and Perspectives
Yuan Xue, Yuan-Chen Guo, Han Zhang +3
In many applications of computer graphics, art and design, it is desirable for a user to provide intuitive non-image input, such as text, sketch, stroke, graph or layout, and have…
Learning Implicit Glyph Shape Representation
Ying-Tian Liu, Yuan-Chen Guo, Yi-Xiao Li +2
In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph…
Sketch2Model: View-Aware 3D Modeling from Single Free-Hand Sketches
Song-Hai Zhang, Yuan-Chen Guo, Qing-Wen Gu
We investigate the problem of generating 3D meshes from single free-hand sketches, aiming at fast 3D modeling for novice users. It can be regarded as a single-view reconstruction p…
TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields
Tian-Xing Xu, Yuan-Chen Guo, Zhiqiang Li +3
Place recognition plays an essential role in the field of autonomous driving and robot navigation. Point cloud based methods mainly focus on extracting global descriptors from loca…