12 citations · 19 across the 16 of their papers we have counts for
11 papers · 1 filter
CoaG: Cylinders on a Grid for Coarse 3D Layout Control in Video Generation
Zhangsihao Yang, Mengyi Shan
We ask how little geometry a person has to draw to control both where people stand and where the camera moves in a generated video. Our answer is a ground plane and one cylinder pe…
How Effective Can Dropout Be in Multiple Instance Learning ?
Wenhui Zhu, Peijie Qiu, Xiwen Chen +4
Multiple Instance Learning (MIL) is a popular weakly-supervised method for various applications, with a particular interest in histological whole slide image (WSI) classification.…
AMG: Avatar Motion Guided Video Generation
Zhangsihao Yang, Mengyi Shan, Mohammad Farazi +4
Human video generation task has gained significant attention with the advancement of deep generative models. Generating realistic videos with human movements is challenging in natu…
OmniMotionGPT: Animal Motion Generation with Limited Data
Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan +6
Our paper aims to generate diverse and realistic animal motion sequences from textual descriptions, without a large-scale animal text-motion dataset. While the task of text-driven…
Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation
Zhangsihao Yang, Mengwei Ren, Kaize Ding +2
Pretraining CNN models (i.e., UNet) through self-supervision has become a powerful approach to facilitate medical image segmentation under low annotation regimes. Recent contrastiv…
Envisioning a Next Generation Extended Reality Conferencing System with Efficient Photorealistic Human Rendering
Chuanyue Shen, Letian Zhang, Zhangsihao Yang +4
Meeting online is becoming the new normal. Creating an immersive experience for online meetings is a necessity towards more diverse and seamless environments. Efficient photorealis…
TetCNN: Convolutional Neural Networks on Tetrahedral Meshes
Mohammad Farazi, Zhangsihao Yang, Wenhui Zhu +2
Convolutional neural networks (CNN) have been broadly studied on images, videos, graphs, and triangular meshes. However, it has seldom been studied on tetrahedral meshes. Given the…
Anisotropic Multi-Scale Graph Convolutional Network for Dense Shape Correspondence
Mohammad Farazi, Wenhui Zhu, Zhangsihao Yang +1
This paper studies 3D dense shape correspondence, a key shape analysis application in computer vision and graphics. We introduce a novel hybrid geometric deep learning-based model…
Continuous Geodesic Convolutions for Learning on 3D Shapes
Zhangsihao Yang, Or Litany, Tolga Birdal +2
The majority of descriptor-based methods for geometric processing of non-rigid shape rely on hand-crafted descriptors. Recently, learning-based techniques have been shown effective…
3D Conceptual Design Using Deep Learning
Zhangsihao Yang, Haoliang Jiang, Zou Lan
This article proposes a data-driven methodology to achieve a fast design support, in order to generate or develop novel designs covering multiple object categories. This methodolog…
Data-driven Upsampling of Point Clouds
Wentai Zhang, Haoliang Jiang, Zhangsihao Yang +3
High quality upsampling of sparse 3D point clouds is critically useful for a wide range of geometric operations such as reconstruction, rendering, meshing, and analysis. In this pa…