Search Results for author:
Found 10 papers, 4 papers with code
Virtual Pets: Animatable Animal Generation in 3D Scenes
Toward unlocking the potential of generative models in immersive 4D experiences, we introduce Virtual Pet, a novel pipeline to model realistic and diverse motions for target animal species within a 3D environment.
DreaMo: Articulated 3D Reconstruction From A Single Casual Video
In this work, we study articulated 3D shape reconstruction from a single and casually captured internet video, where the subject's view coverage is incomplete.
SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation
To enable interactive generation, our method supports a variety of input modalities that can be easily provided by a human, including images, text, partially observed shapes and combinations of these, further allowing to adjust the strength of each input.
AutoSDF: Shape Priors for 3D Completion, Reconstruction and Generation
This enables us to represent distributions over 3D shapes conditioned on information from an arbitrary set of spatially anchored query locations and thus perform shape completion in such arbitrary settings (e. g., generating a complete chair given only a view of the back leg).
InOut: Diverse Image Outpainting via GAN Inversion
Existing image outpainting methods pose the problem as a conditional image-to-image translation task, often generating repetitive structures and textures by replicating the content available in the input image.
InfinityGAN: Towards Infinite-Pixel Image Synthesis
We present a novel framework, InfinityGAN, for arbitrary-sized image generation.
Ranked #1 on
Scene Generation
on OSM
In&Out : Diverse Image Outpainting via GAN Inversion
Existing image outpainting methods pose the problem as a conditional image-to-image translation task, often generating repetitive structures and textures by replicating the content available in the input image.
Controllable Image Synthesis via SegVAE
We also apply an off-the-shelf image-to-image translation model to generate realistic RGB images to better understand the quality of the synthesized semantic maps.
Point-to-Point Video Generation
We introduce point-to-point video generation that controls the generation process with two control points: the targeted start- and end-frames.
Radiotherapy Target Contouring with Convolutional Gated Graph Neural Network
Instead, inspired by the treating methodology of considering meaningful information across slices, we used Gated Graph Neural Network to frame this problem more efficiently.
