25 citations · 111 across the 31 of their papers we have counts for
22 papers · 1 filter
Reverse Prompt: Cracking the Recipe Inside Text-to-Image Generation
Zhiyao Ren, Yibing Zhan, Baosheng Yu +1
Text-to-image generation has become increasingly popular, but achieving the desired images often requires extensive prompt engineering. In this paper, we explore how to decode text…
Self-Supervised Learning for Detecting AI-Generated Faces as Anomalies
Mian Zou, Baosheng Yu, Yibing Zhan +1
The detection of AI-generated faces is commonly approached as a binary classification task. Nevertheless, the resulting detectors frequently struggle to adapt to novel AI face gene…
Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approach
Mian Zou, Baosheng Yu, Yibing Zhan +2
In recent years, the multimedia forensics and security community has seen remarkable progress in multitask learning for DeepFake (i.e., face forgery) detection. The prevailing appr…
Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Method
Mian Zou, Baosheng Yu, Yibing Zhan +2
In recent years, deep learning has greatly streamlined the process of manipulating photographic face images. Aware of the potential dangers, researchers have developed various tool…
Deep Learning-Based Point Cloud Registration: A Comprehensive Survey and Taxonomy
Yu-Xin Zhang, Jie Gui, Baosheng Yu +4
Point cloud registration involves determining a rigid transformation to align a source point cloud with a target point cloud. This alignment is fundamental in applications such as…
PointHR: Exploring High-Resolution Architectures for 3D Point Cloud Segmentation
Haibo Qiu, Baosheng Yu, Yixin Chen +1
Significant progress has been made recently in point cloud segmentation utilizing an encoder-decoder framework, which initially encodes point clouds into low-resolution representat…
ChartDETR: A Multi-shape Detection Network for Visual Chart Recognition
Wenyuan Xue, Dapeng Chen, Baosheng Yu +3
Visual chart recognition systems are gaining increasing attention due to the growing demand for automatically identifying table headers and values from chart images. Current method…
Patch-Wise Point Cloud Generation: A Divide-and-Conquer Approach
Cheng Wen, Baosheng Yu, Rao Fu +1
A generative model for high-fidelity point clouds is of great importance in synthesizing 3d environments for applications such as autonomous driving and robotics. Despite the recen…
Free-Form Composition Networks for Egocentric Action Recognition
Haoran Wang, Qinghua Cheng, Baosheng Yu +4
Egocentric action recognition is gaining significant attention in the field of human action recognition. In this paper, we address data scarcity issue in egocentric action recognit…
Collect-and-Distribute Transformer for 3D Point Cloud Analysis
Haibo Qiu, Baosheng Yu, Dacheng Tao
Remarkable advancements have been made recently in point cloud analysis through the exploration of transformer architecture, but it remains challenging to effectively learn local a…
Compositional 3D Human-Object Neural Animation
Zhi Hou, Baosheng Yu, Dacheng Tao
Human-object interactions (HOIs) are crucial for human-centric scene understanding applications such as human-centric visual generation, AR/VR, and robotics. Since existing methods…
MeshMAE: Masked Autoencoders for 3D Mesh Data Analysis
Yaqian Liang, Shanshan Zhao, Baosheng Yu +2
Recently, self-supervised pre-training has advanced Vision Transformers on various tasks w.r.t. different data modalities, e.g., image and 3D point cloud data. In this paper, we ex…
GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation
Haibo Qiu, Baosheng Yu, Dacheng Tao
Point cloud semantic segmentation from projected views, such as range-view (RV) and bird's-eye-view (BEV), has been intensively investigated. Different views capture different info…
BatchFormerV2: Exploring Sample Relationships for Dense Representation Learning
Zhi Hou, Baosheng Yu, Chaoyue Wang +2
Attention mechanisms have been very popular in deep neural networks, where the Transformer architecture has achieved great success in not only natural language processing but also…
Contrastive Boundary Learning for Point Cloud Segmentation
Liyao Tang, Yibing Zhan, Zhe Chen +2
Point cloud segmentation is fundamental in understanding 3D environments. However, current 3D point cloud segmentation methods usually perform poorly on scene boundaries, which deg…
Hyper-relationship Learning Network for Scene Graph Generation
Yibing Zhan, Zhi Chen, Jun Yu +3
Generating informative scene graphs from images requires integrating and reasoning from various graph components, i.e., objects and relationships. However, current scene graph gene…
Discovering Human-Object Interaction Concepts via Self-Compositional Learning
Zhi Hou, Baosheng Yu, Dacheng Tao
A comprehensive understanding of human-object interaction (HOI) requires detecting not only a small portion of predefined HOI concepts (or categories) but also other reasonable HOI…
Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers
Lixiang Ru, Yibing Zhan, Baosheng Yu +1
Weakly-supervised semantic segmentation (WSSS) with image-level labels is an important and challenging task. Due to the high training efficiency, end-to-end solutions for WSSS have…
Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation
Chao Chen, Yibing Zhan, Baosheng Yu +3
Scene Graph Generation (SGG) aims to build a structured representation of a scene using objects and pairwise relationships, which benefits downstream tasks. However, current SGG me…
SynFace: Face Recognition with Synthetic Data
Haibo Qiu, Baosheng Yu, Dihong Gong +3
With the recent success of deep neural networks, remarkable progress has been achieved on face recognition. However, collecting large-scale real-world training data for face recogn…
TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition
Wenyuan Xue, Baosheng Yu, Wen Wang +2
A table arranging data in rows and columns is a very effective data structure, which has been widely used in business and scientific research. Considering large-scale tabular data…
Affordance Transfer Learning for Human-Object Interaction Detection
Zhi Hou, Baosheng Yu, Yu Qiao +2
Reasoning the human-object interactions (HOI) is essential for deeper scene understanding, while object affordances (or functionalities) are of great importance for human to discov…