205 citations · 301 across the 11 of their papers we have counts for
11 papers
Faster 3D Gaussian Splatting Convergence via Structure-Aware Densification
Linjie Lyu, Ayush Tewari, Jianchun Chen +2
3D Gaussian Splatting has emerged as a powerful scene representation for real-time novel-view synthesis. However, its standard adaptive density control relies on screen-space posit…
Splat the Net: Radiance Fields with Splattable Neural Primitives
Xilong Zhou, Bao-Huy Nguyen, Loïc Magne +3
Radiance fields have emerged as a predominant representation for modeling 3D scene appearance. Neural formulations such as Neural Radiance Fields provide high expressivity but requ…
Marching Neurons: Accurate Surface Extraction for Neural Implicit Shapes
Christian Stippel, Felix Mujkanovic, Thomas Leimkühler +1
Accurate surface geometry representation is crucial in 3D visual computing. Explicit representations, such as polygonal meshes, and implicit representations, like signed distance f…
Learning Neural Antiderivatives
Fizza Rubab, Ntumba Elie Nsampi, Martin Balint +4
Neural fields offer continuous, learnable representations that extend beyond traditional discrete formats in visual computing. We study the problem of learning neural representatio…
LEDiff: Latent Exposure Diffusion for HDR Generation
Chao Wang, Zhihao Xia, Thomas Leimkuehler +2
While consumer displays increasingly support more than 10 stops of dynamic range, most image assets such as internet photographs and generative AI content remain limited to 8-bit l…
Bracket Diffusion: HDR Image Generation by Consistent LDR Denoising
Mojtaba Bemana, Thomas Leimkühler, Karol Myszkowski +2
We demonstrate generating HDR images using the concerted action of multiple black-box, pre-trained LDR image diffusion models. Relying on a pre-trained LDR generative diffusion mod…
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold
Xingang Pan, Ayush Tewari, Thomas Leimkühler +3
Synthesizing visual content that meets users' needs often requires flexible and precise controllability of the pose, shape, expression, and layout of the generated objects. Existin…
Neural Field Convolutions by Repeated Differentiation
Ntumba Elie Nsampi, Adarsh Djeacoumar, Hans-Peter Seidel +2
Neural fields are evolving towards a general-purpose continuous representation for visual computing. Yet, despite their numerous appealing properties, they are hardly amenable to s…
Neural Point Catacaustics for Novel-View Synthesis of Reflections
Georgios Kopanas, Thomas Leimkühler, Gilles Rainer +2
View-dependent effects such as reflections pose a substantial challenge for image-based and neural rendering algorithms. Above all, curved reflectors are particularly hard, as they…
FreeStyleGAN: Free-view Editable Portrait Rendering with the Camera Manifold
Thomas Leimkühler, George Drettakis
Current Generative Adversarial Networks (GANs) produce photorealistic renderings of portrait images. Embedding real images into the latent space of such models enables high-level i…
Point-Based Neural Rendering with Per-View Optimization
Georgios Kopanas, Julien Philip, Thomas Leimkühler +1
There has recently been great interest in neural rendering methods. Some approaches use 3D geometry reconstructed with Multi-View Stereo (MVS) but cannot recover from the errors of…