Papers

RoDynRF: Robust Dynamic Radiance Fields Members Public

In this work, the authors address the robustness issue of dynamic radiance field reconstruction methods by jointly estimating the static and dynamic radiance fields along with the camera parameters (poses and focal length). Learn how they do it!

Sophia
Sophia
Papers

AgileAvatar: Stylized 3D Avatar Creation via Cascaded Domain Bridging Members Public

AgileAvatar is a novel self-supervised learning framework to create high-quality stylized 3D avatars with a mix of continuous and discrete parameters. To ensure the discrete parameters are optimized, a cascaded relaxation-and-search pipeline is implemented.

Sophia
Sophia
Papers

Box2Mask: Box-supervised Instance Segmentation via Level-set Evolution Members Public

Box2Mask is a novel single-shot instance segmentation approach, which integrates the classical level-set evolution model into deep neural network learning to achieve accurate mask prediction with only bounding box supervision. Check the paper out!

Sophia
Sophia
Papers

Zero-Shot Text-Guided Object Generation with Dream Fields Members Public

Dream Fields can generate the geometry and color of a wide range of objects without 3D supervision. It combines neural rendering with multi-modal image and text representations to synthesize diverse 3D objects solely from natural language descriptions. Take a look!

Sophia
Sophia
Papers

InstantAvatar: Learning Avatars from Monocular Video in 60 Seconds Members Public

InstantAvatar is a system that can reconstruct human avatars from a monocular video within seconds, and these avatars can be animated and rendered at an interactive rate. It converges 130x faster and can be trained in minutes instead of hours, way faster than competitors.

Sophia
Sophia
Papers

Scalable Diffusion Models with Transformers Members Public

In this work, the researchers explore a new class of diffusion models based on the transformer architecture; train latent diffusion models, replacing the U-Net backbone with a transformer that operates on latent patches; and analyze the scalability of Diffusion Transformers (DiTs).

Sophia
Sophia
Papers

NeRF-Art: Text-Driven Neural Radiance Fields Stylization Members Public

Neural radiance fields (NeRF) enable high-quality novel view synthesis. Editing NeRF, however, remains challenging. In this paper, the authors present NeRF-Art, a text-guided NeRF stylization approach that manipulates the style of a pre-trained NeRF model with a single text prompt.

Sophia
Sophia
Papers

ECON: Explicit Clothed humans Obtained from Normals Members Public

ECON combines the best aspects of implicit and explicit surfaces to infer high-fidelity 3D humans, even with loose clothing or in challenging poses. ECON is more accurate than the state of the art. Perceptual studies also show that ECON’s perceived realism is better by a large margin.

Sophia
Sophia
Papers