88 citations · 423 across the 74 of their papers we have counts for
25 papers · 1 filter
HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles
Vanessa Sklyarova, Egor Zakharov, Otmar Hilliges +2
We present HAAR, a new strand-based generative model for 3D human hairstyles. Specifically, based on textual inputs, HAAR produces 3D hairstyles that could be used as production-le…
Leveraging Driver Field-of-View for Multimodal Ego-Trajectory Prediction
M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel +5
Understanding drivers' decision-making is crucial for road safety. Although predicting the ego-vehicle's path is valuable for driver-assistance systems, existing methods mainly foc…
HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video
Zicong Fan, Maria Parelli, Maria Eleni Kadoglou +4
Since humans interact with diverse objects every day, the holistic 3D capture of these interactions is important to understand and model human behaviour. However, most existing met…
PALM: Predicting Actions through Language Models
Sanghwan Kim, Daoji Huang, Yongqin Xian +3
Understanding human activity is a crucial yet intricate task in egocentric vision, a field that focuses on capturing visual perspectives from the camera wearer's viewpoint. Traditi…
A Unified Approach for Text- and Image-guided 4D Scene Generation
Yufeng Zheng, Xueting Li, Koki Nagano +4
Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of t…
SiTH: Single-view Textured Human Reconstruction with Image-Conditioned Diffusion
Hsuan-I Ho, Jie Song, Otmar Hilliges
A long-standing goal of 3D human reconstruction is to create lifelike and fully detailed 3D humans from single-view images. The main challenge lies in inferring unknown body shapes…
SynH2R: Synthesizing Hand-Object Motions for Learning Human-to-Robot Handovers
Sammy Christen, Lan Feng, Wei Yang +3
Vision-based human-to-robot handover is an important and challenging task in human-robot interaction. Recent work has attempted to train robot policies by interacting with dynamic…
FLARE: Fast Learning of Animatable and Relightable Mesh Avatars
Shrisha Bharadwaj, Yufeng Zheng, Otmar Hilliges +2
Our goal is to efficiently learn personalized animatable 3D head avatars from videos that are geometrically accurate, realistic, relightable, and compatible with current rendering…
PACE: Human and Camera Motion Estimation from in-the-wild Videos
Muhammed Kocabas, Ye Yuan, Pavlo Molchanov +5
We present a method to estimate human motion in a global scene from moving cameras. This is a highly challenging task due to the coupling of human and camera motions in the video.…
CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley +2
While conditional diffusion models are known to have good coverage of the data distribution, they still face limitations in output diversity, particularly when sampled with a high…
Preface: A Data-driven Volumetric Prior for Few-shot Ultra High-resolution Face Synthesis
Marcel C. Bühler, Kripasindhu Sarkar, Tanmay Shah +8
NeRFs have enabled highly realistic synthesis of human faces including complex appearance and reflectance effects of hair and skin. These methods typically require a large number o…
Physically Plausible Full-Body Hand-Object Interaction Synthesis
Jona Braun, Sammy Christen, Muhammed Kocabas +2
We propose a physics-based method for synthesizing dexterous hand-object interactions in a full-body setting. While recent advancements have addressed specific facets of human-obje…
ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulation
Hui Zhang, Sammy Christen, Zicong Fan +4
We present ArtiGrasp, a novel method to synthesize bi-manual hand-object interactions that include grasping and articulation. This task is challenging due to the diversity of the g…
EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild
Manuel Kaufmann, Jie Song, Chen Guo +5
We present EMDB, the Electromagnetic Database of Global 3D Human Pose and Shape in the Wild. EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters wi…
Palm: Predicting Actions through Language Models @ Ego4D Long-Term Action Anticipation Challenge 2023
Daoji Huang, Otmar Hilliges, Luc Van Gool +1
We present Palm, a solution to the Long-Term Action Anticipation (LTA) task utilizing vision-language and large language models. Given an input video with annotated action periods,…
EFE: End-to-end Frame-to-Gaze Estimation
Haldun Balim, Seonwook Park, Xi Wang +2
Despite the recent development of learning-based gaze estimation methods, most methods require one or more eye or face region crops as inputs and produce a gaze direction vector as…
AG3D: Learning to Generate 3D Avatars from 2D Image Collections
Zijian Dong, Xu Chen, Jinlong Yang +3
While progress in 2D generative models of human appearance has been rapid, many applications require 3D avatars that can be animated and rendered. Unfortunately, most existing meth…
Learning Locally Editable Virtual Humans
Hsuan-I Ho, Lixin Xue, Jie Song +1
In this paper, we propose a novel hybrid representation and end-to-end trainable network architecture to model fully editable and customizable neural avatars. At the core of our wo…
Learning Human-to-Robot Handovers from Point Clouds
Sammy Christen, Wei Yang, Claudia Pérez-D'Arpino +3
We propose the first framework to learn control policies for vision-based human-to-robot handovers, a critical task for human-robot interaction. While research in Embodied AI has m…
Hi4D: 4D Instance Segmentation of Close Human Interaction
Yifei Yin, Chen Guo, Manuel Kaufmann +3
We propose Hi4D, a method and dataset for the automatic analysis of physically close human-human interaction under prolonged contact. Robustly disentangling several in-contact subj…
Efficient Learning of High Level Plans from Play
Núria Armengol Urpí, Marco Bagatella, Otmar Hilliges +2
Real-world robotic manipulation tasks remain an elusive challenge, since they involve both fine-grained environment interaction, as well as the ability to plan for long-horizon goa…
X-Avatar: Expressive Human Avatars
Kaiyue Shen, Chen Guo, Manuel Kaufmann +4
We present X-Avatar, a novel avatar model that captures the full expressiveness of digital humans to bring about life-like experiences in telepresence, AR/VR and beyond. Our method…
Human from Blur: Human Pose Tracking from Blurry Images
Yiming Zhao, Denys Rozumnyi, Jie Song +3
We propose a method to estimate 3D human poses from substantially blurred images. The key idea is to tackle the inverse problem of image deblurring by modeling the forward problem…
Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition
Chen Guo, Tianjian Jiang, Xu Chen +2
We present Vid2Avatar, a method to learn human avatars from monocular in-the-wild videos. Reconstructing humans that move naturally from monocular in-the-wild videos is difficult.…