9 citations · 13 across the 7 of their papers we have counts for
7 papers
Multi-view Image Diffusion via Coordinate Noise and Fourier Attention
Justin Theiss, Norman Müller, Daeil Kim +1
Recently, text-to-image generation with diffusion models has made significant advancements in both higher fidelity and generalization capabilities compared to previous baselines. H…
Target-Aware Language Modeling via Granular Data Sampling
Ernie Chang, Pin-Jie Lin, Yang Li +6
Language model pretraining generally targets a broad range of use cases and incorporates data from diverse sources. However, there are instances where we desire a model that excels…
Generalizable Human Gaussians for Sparse View Synthesis
Youngjoong Kwon, Baole Fang, Yixing Lu +9
Recent progress in neural rendering has brought forth pioneering methods, such as NeRF and Gaussian Splatting, which revolutionize view rendering across various domains like AR/VR,…
Towards Realistic Generative 3D Face Models
Aashish Rai, Hiresh Gupta, Ayush Pandey +6
In recent years, there has been significant progress in 2D generative face models fueled by applications such as animation, synthetic data generation, and digital avatars. However,…
Unpaired Image Translation via Vector Symbolic Architectures
Justin Theiss, Jay Leverett, Daeil Kim +1
Image-to-image translation has played an important role in enabling synthetic data for computer vision. However, if the source and target domains have a large semantic mismatch, ex…
Controllable 3D Generative Adversarial Face Model via Disentangling Shape and Appearance
Fariborz Taherkhani, Aashish Rai, Quankai Gao +6
3D face modeling has been an active area of research in computer vision and computer graphics, fueling applications ranging from facial expression transfer in virtual avatars to sy…
RarePlanes: Synthetic Data Takes Flight
Jacob Shermeyer, Thomas Hossler, Adam Van Etten +3
RarePlanes is a unique open-source machine learning dataset that incorporates both real and synthetically generated satellite imagery. The RarePlanes dataset specifically focuses o…