Search Results for author:
Found 14 papers, 7 papers with code
GenFusion: Closing the Loop between Reconstruction and Generation via Videos
Moreover, we propose a cyclical fusion pipeline that iteratively adds restoration frames from the generative model to the training set, enabling progressive expansion and addressing the viewpoint saturation limitations seen in previous reconstruction and generation pipelines.
Space-time 2D Gaussian Splatting for Accurate Surface Reconstruction under Complex Dynamic Scenes
To tackle the dynamic contents and the occlusions in complex scenes, we present a space-time 2D Gaussian Splatting approach.
GeoFormer: Learning Point Cloud Completion with Tri-Plane Integrated Transformer
In this paper, we introduce a GeoFormer that simultaneously enhances the global geometric structure of the points and improves the local details.
Surfel-based Gaussian Inverse Rendering for Fast and Relightable Dynamic Human Reconstruction from Monocular Video
Efficient and accurate reconstruction of a relightable, dynamic clothed human avatar from a monocular video is crucial for the entertainment industry.
Continual Learning for Temporal-Sensitive Question Answering
In this study, we explore an emerging research area of Continual Learning for Temporal Sensitive Question Answering (CLTSQA).
2D Gaussian Splatting for Geometrically Accurate Radiance Fields
3D Gaussian Splatting (3DGS) has recently revolutionized radiance field reconstruction, achieving high quality novel view synthesis and fast rendering speed without baking.
Mip-Splatting: Alias-free 3D Gaussian Splatting
Recently, 3D Gaussian Splatting has demonstrated impressive novel view synthesis results, reaching high fidelity and efficiency.
TSP-Transformer: Task-Specific Prompts Boosted Transformer for Holistic Scene Understanding
Holistic scene understanding includes semantic segmentation, surface normal estimation, object boundary detection, depth estimation, etc.
Omni-Line-of-Sight Imaging for Holistic Shape Reconstruction
The core of our method is to put the object nearby diffuse walls and augment the LOS scan in the front view with the NLOS scans from the surrounding walls, which serve as virtual ``mirrors'' to trap lights toward the object.
3D-aware Image Generation using 2D Diffusion Models
In this paper, we introduce a novel 3D-aware image generation method that leverages 2D diffusion models.
Enhancing Non-line-of-sight Imaging via Learnable Inverse Kernel and Attention Mechanisms
Recovering information from non-line-of-sight (NLOS) imaging is a computationally-intensive inverse problem.
PREF: Phasorial Embedding Fields for Compact Neural Representations
We present an efficient frequency-based neural representation termed PREF: a shallow MLP augmented with a phasor volume that covers significant border spectra than previous Fourier feature mapping or Positional Encoding.
Look Before You Leap: Learning Landmark Features for One-Stage Visual Grounding
Then we combine the contextual information from the landmark feature convolution module with the target's visual features for grounding.
