1 citations · 1 across the 2 of their papers we have counts for
6 papers
PixGS: Pixel-Space Diffusion for Direct 3D Gaussian Splat Generation
Cao Duy, Phong Nguyen-Ha
Recent advances in 3D content generation from text or images have achieved impressive results, yet view inconsistency from 2D generators and the scarcity of high-quality 3D data re…
Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation
Long Vu, Tan Ngo, Animesh Karnewar +5
Modern image-and-text-to-video diffusion models can synthesize highly realistic videos by iteratively denoising an initial Gaussian noise tensor conditioned on reference image and…
An End-to-End Depth-Based Pipeline for Selfie Image Rectification
Ahmed Alhawwary, Janne Mustaniemi, Phong Nguyen-Ha +1
Portraits or selfie images taken from a close distance typically suffer from perspective distortion. In this paper, we propose an end-to-end deep learning-based rectification pipel…
Sequential View Synthesis with Transformer
Phong Nguyen-Ha, Lam Huynh, Esa Rahtu +1
This paper addresses the problem of novel view synthesis by means of neural rendering, where we are interested in predicting the novel view at an arbitrary camera pose based on a g…
Guiding Monocular Depth Estimation Using Depth-Attention Volume
Lam Huynh, Phong Nguyen-Ha, Jiri Matas +2
Recovering the scene depth from a single image is an ill-posed problem that requires additional priors, often referred to as monocular depth cues, to disambiguate different 3D inte…
Predicting Novel Views Using Generative Adversarial Query Network
Phong Nguyen-Ha, Lam Huynh, Esa Rahtu +1
The problem of predicting a novel view of the scene using an arbitrary number of observations is a challenging problem for computers as well as for humans. This paper introduces th…