7 papers
Where Will They Go? Modelling Multimodal Pedestrian Manoeuvres from Ego-centric Videos
Yuxuan Xie, Nicolas Pugeault, Chongfeng Wei +2
Pedestrian trajectory prediction from an on-board ego-centric camera is challenging since it depends on complex interactions with vehicles and scene context, as well as the intenti…
Splat-Portrait: Generalizing Talking Heads with Gaussian Splatting
Tong Shi, Melonie de Almeida, Daniela Ivanova +2
Talking Head Generation aims at synthesizing natural-looking talking videos from speech and a single portrait image. Previous 3D talking head generation methods have relied on doma…
A Convolutional Neural Deferred Shader for Physics Based Rendering
Zhuo He, Yingdong Ru, Qianying Liu +2
Recent advances in neural rendering have achieved impressive results on photorealistic shading and relighting, by using a multilayer perceptron (MLP) as a regression model to learn…
Flow and Depth Assisted Video Prediction with Latent Transformer
Eliyas Suleyman, Paul Henderson, Eksan Firkat +1
Video prediction is a fundamental task for various downstream applications, including robotics and world modeling. Although general video prediction models have achieved remarkable…
Beyond Reconstruction: A Physics Based Neural Deferred Shader for Photo-realistic Rendering
Zhuo He, Paul Henderson, Nicolas Pugeault
Deep learning based rendering has achieved major improvements in photo-realistic image synthesis, with potential applications including visual effects in movies and photo-realistic…
Generative Fields: Uncovering Hierarchical Feature Control for StyleGAN via Inverted Receptive Fields
Zhuo He, Paul Henderson, Nicolas Pugeault
StyleGAN has demonstrated the ability of GANs to synthesize highly-realistic faces of imaginary people from random noise. One limitation of GAN-based image generation is the diffic…