Search Results for author: Christian Haene

Found 9 papers, 2 papers with code

Personalized Face Inpainting with Diffusion Models by Parallel Visual Attention

no code implementations6 Dec 2023 Jianjin Xu, Saman Motamed, Praneetha Vaddamanu, Chen Henry Wu, Christian Haene, Jean-Charles Bazin, Fernando de la Torre

Specifically, we insert parallel attention matrices to each cross-attention module in the denoising network, which attends to features extracted from reference images by an identity encoder.

Denoising Facial Inpainting

SSDNeRF: Semantic Soft Decomposition of Neural Radiance Fields

no code implementations7 Dec 2022 Siddhant Ranade, Christoph Lassner, Kai Li, Christian Haene, Shen-Chi Chen, Jean-Charles Bazin, Sofien Bouaziz

Neural Radiance Fields (NeRFs) encode the radiance in a scene parameterized by the scene's plenoptic function.

Video Editing

Multiresolution Deep Implicit Functions for 3D Shape Representation

no code implementations ICCV 2021 Zhang Chen, yinda zhang, Kyle Genova, Sean Fanello, Sofien Bouaziz, Christian Haene, Ruofei Du, Cem Keskin, Thomas Funkhouser, Danhang Tang

To the best of our knowledge, MDIF is the first deep implicit function model that can at the same time (1) represent different levels of detail and allow progressive decoding; (2) support both encoder-decoder inference and decoder-only latent optimization, and fulfill multiple applications; (3) perform detailed decoder-only shape completion.

3D Reconstruction 3D Shape Representation +1

RePose: Learning Deep Kinematic Priors for Fast Human Pose Estimation

no code implementations10 Feb 2020 Hossam Isack, Christian Haene, Cem Keskin, Sofien Bouaziz, Yuri Boykov, Shahram Izadi, Sameh Khamis

At the coarsest resolution, and in a manner similar to classical part-based approaches, we leverage the kinematic structure of the human body to propagate convolutional feature updates between the keypoints or body parts.

Pose Estimation

Learning Independent Object Motion from Unlabelled Stereoscopic Videos

no code implementations CVPR 2019 Zhe Cao, Abhishek Kar, Christian Haene, Jitendra Malik

Unlike prior learning based work which has focused on predicting dense pixel-wise optical flow field and/or a depth map for each image, we propose to predict object instance specific 3D scene flow maps and instance masks from which we are able to derive the motion direction and speed for each object instance.

Object Optical Flow Estimation

Semantic 3D Reconstruction with Continuous Regularization and Ray Potentials Using a Visibility Consistency Constraint

1 code implementation CVPR 2016 Nikolay Savinov, Christian Haene, Lubor Ladicky, Marc Pollefeys

We propose an approach for dense semantic 3D reconstruction which uses a data term that is defined as potentials over viewing rays, combined with continuous surface area penalization.

3D Reconstruction

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