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Liang An

9 accepted papers

2026

4DEquine: Disentangling Motion and Appearance for 4D Equine Reconstruction from Monocular Video

CVPR 2026

4D reconstruction of equine family (e.g. horses) from monocular video is important for animal welfare. Previous mainstream 4D animal reconstruction methods require joint optimization of motion and appearance over a whole video, which is time-consuming and sensitive to incomplete observation. In this

Cited by 0SourceScholar
2026

MoReMouse: Monocular Reconstruction of Laboratory Mouse

AAAI 2026technical

Laboratory mice, particularly the C57BL/6 strain, are essential animal models in biomedical research. However, accurate 3D surface motion reconstruction of mice remains a significant challenge due to their complex non-rigid deformations, textureless fur-covered surfaces, and the lack of realistic 3D

Cited by 0SourcePDFScholar
2026

Monocular Mesh Recovery and Body Measurement of Female Saanen Goats

AAAI 2026technical

The lactation performance of Saanen dairy goats, renowned for their high milk yield, is intrinsically linked to their body size, making accurate 3D body measurement essential for assessing milk production potential, yet existing reconstruction methods lack goat-specific authentic 3D data. To address

Cited by 0SourcePDFScholar
2023

Delving Deep into Pixel Alignment Feature for Accurate Multi-View Human Mesh Recovery

AAAI 2023technical

Regression-based methods have shown high efficiency and effectiveness for multi-view human mesh recovery. The key components of a typical regressor lie in the feature extraction of input views and the fusion of multi-view features. In this paper, we present Pixel-aligned Feedback Fusion (PaFF) for a…

2023

Triangulation Residual Loss for Data-efficient 3D Pose Estimation

NeurIPS 2023poster

This paper presents Triangulation Residual loss (TR loss) for multiview 3D pose estimation in a data-efficient manner. Existing 3D supervised models usually require large-scale 3D annotated datasets, but the amount of existing data is still insufficient to train supervised models to achieve ideal pe…

2022

Interacting Attention Graph for Single Image Two-Hand Reconstruction

CVPR 2022oral

Graph convolutional network (GCN) has achieved great success in single hand reconstruction task, while interacting two-hand reconstruction by GCN remains unexplored. In this paper, we present Interacting Attention Graph Hand (IntagHand), the first graph convolution based network that reconstructs tw…

Cited by 133PDFcodeScholar
2021

Lightweight Multi-Person Total Motion Capture Using Sparse Multi-View Cameras

ICCV 2021poster

Multi-person total motion capture is extremely challenging when it comes to handle severe occlusions, different reconstruction granularities from body to face and hands, drastically changing observation scales and fast body movements. To overcome these challenges above, we contribute a lightweight t…

Cited by 64PDFScholar
2020

4D Association Graph for Realtime Multi-Person Motion Capture Using Multiple Video Cameras

CVPR 2020oral

his paper contributes a novel realtime multi-person motion capture algorithm using multiview video inputs. Due to the heavy occlusions and closely interacting motions in each view, joint optimization on the multiview images and multiple temporal frames is indispensable, which brings up the essential…

Cited by 104PDFcodeScholar
2018

DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNs

ECCV 2018poster

Consumer depth sensors are more and more popular and come to our daily lives marked by its recent integration in the latest Iphone X. However, they still suffer from heavy noises which limit their applications. Although plenty of progresses have been made to reduce the noises and boost geometric det…