30 citations · 99 across the 18 of their papers we have counts for
17 papers · 1 filter
Human-Aware 3D Scene Generation with Spatially-constrained Diffusion Models
Xiaolin Hong, Hongwei Yi, Fazhi He +1
Generating 3D scenes from human motion sequences supports numerous applications, including virtual reality and architectural design. However, previous auto-regression-based human-a…
Generating Human Interaction Motions in Scenes with Text Control
Hongwei Yi, Justus Thies, Michael J. Black +2
We present TeSMo, a method for text-controlled scene-aware motion generation based on denoising diffusion models. Previous text-to-motion methods focus on characters in isolation w…
DECO: Dense Estimation of 3D Human-Scene Contact In The Wild
Shashank Tripathi, Agniv Chatterjee, Jean-Claude Passy +3
Understanding how humans use physical contact to interact with the world is key to enabling human-centric artificial intelligence. While inferring 3D contact is crucial for modelin…
POCO: 3D Pose and Shape Estimation with Confidence
Sai Kumar Dwivedi, Cordelia Schmid, Hongwei Yi +2
The regression of 3D Human Pose and Shape (HPS) from an image is becoming increasingly accurate. This makes the results useful for downstream tasks like human action recognition or…
TeCH: Text-guided Reconstruction of Lifelike Clothed Humans
Yangyi Huang, Hongwei Yi, Yuliang Xiu +4
Despite recent research advancements in reconstructing clothed humans from a single image, accurately restoring the "unseen regions" with high-level details remains an unsolved cha…
GraMMaR: Ground-aware Motion Model for 3D Human Motion Reconstruction
Sihan Ma, Qiong Cao, Hongwei Yi +2
Demystifying complex human-ground interactions is essential for accurate and realistic 3D human motion reconstruction from RGB videos, as it ensures consistency between the humans…
SLOPER4D: A Scene-Aware Dataset for Global 4D Human Pose Estimation in Urban Environments
Yudi Dai, Yitai Lin, Xiping Lin +6
We present SLOPER4D, a novel scene-aware dataset collected in large urban environments to facilitate the research of global human pose estimation (GHPE) with human-scene interactio…
MIME: Human-Aware 3D Scene Generation
Hongwei Yi, Chun-Hao P. Huang, Shashank Tripathi +3
Generating realistic 3D worlds occupied by moving humans has many applications in games, architecture, and synthetic data creation. But generating such scenes is expensive and labo…
Generating Holistic 3D Human Motion from Speech
Hongwei Yi, Hualin Liang, Yifei Liu +5
This work addresses the problem of generating 3D holistic body motions from human speech. Given a speech recording, we synthesize sequences of 3D body poses, hand gestures, and fac…
One-shot Implicit Animatable Avatars with Model-based Priors
Yangyi Huang, Hongwei Yi, Weiyang Liu +6
Existing neural rendering methods for creating human avatars typically either require dense input signals such as video or multi-view images, or leverage a learned prior from large…
NeRF-Loc: Transformer-Based Object Localization Within Neural Radiance Fields
Jiankai Sun, Yan Xu, Mingyu Ding +5
Neural Radiance Fields (NeRFs) have become a widely-applied scene representation technique in recent years, showing advantages for robot navigation and manipulation tasks. To furth…
Capturing and Inferring Dense Full-Body Human-Scene Contact
Chun-Hao P. Huang, Hongwei Yi, Markus Höschle +5
Inferring human-scene contact (HSC) is the first step toward understanding how humans interact with their surroundings. While detecting 2D human-object interaction (HOI) and recons…
Human-Aware Object Placement for Visual Environment Reconstruction
Hongwei Yi, Chun-Hao P. Huang, Dimitrios Tzionas +5
Humans are in constant contact with the world as they move through it and interact with it. This contact is a vital source of information for understanding 3D humans, 3D scenes, an…
Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking
Jianfeng Yan, Zizhuang Wei, Hongwei Yi +5
In this paper, we propose an efficient and effective dense hybrid recurrent multi-view stereo net with dynamic consistency checking, namely HC-RMVSNet, for accurate dense po…
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud
Hongwei Yi, Shaoshuai Shi, Mingyu Ding +6
3D vehicle detection based on point cloud is a challenging task in real-world applications such as autonomous driving. Despite significant progress has been made, we observe two as…
Learning Depth-Guided Convolutions for Monocular 3D Object Detection
Mingyu Ding, Yuqi Huo, Hongwei Yi +4
3D object detection from a single image without LiDAR is a challenging task due to the lack of accurate depth information. Conventional 2D convolutions are unsuitable for this task…
Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation
Hongwei Yi, Zizhuang Wei, Mingyu Ding +4
n this paper, we propose an effective and efficient pyramid multi-view stereo (MVS) net with self-adaptive view aggregation for accurate and complete dense point cloud reconstructi…