10 citations · 19 across the 9 of their papers we have counts for
8 papers · 1 filter
Descrip3D: Enhancing Large Language Model-based 3D Scene Understanding with Object-Level Text Descriptions
Jintang Xue, Ganning Zhao, Jie-En Yao +5
Understanding 3D scenes goes beyond simply recognizing objects; it requires reasoning about the spatial and semantic relationships between them. Current 3D scene-language models of…
SemST: Semantically Consistent Multi-Scale Image Translation via Structure-Texture Alignment
Ganning Zhao, Wenhui Cui, Suya You +1
Unsupervised image-to-image (I2I) translation learns cross-domain image mapping that transfers input from the source domain to output in the target domain while preserving its sema…
A Study on Improving Realism of Synthetic Data for Machine Learning
Tingwei Shen, Ganning Zhao, Suya You
Synthetic-to-real data translation using generative adversarial learning has achieved significant success in improving synthetic data. Yet, limited studies focus on deep evaluation…
Unsupervised Synthetic Image Refinement via Contrastive Learning and Consistent Semantic-Structural Constraints
Ganning Zhao, Tingwei Shen, Suya You +1
Ensuring the realism of computer-generated synthetic images is crucial to deep neural network (DNN) training. Due to different semantic distributions between synthetic and real-wor…
TGHop: An Explainable, Efficient and Lightweight Method for Texture Generation
Xuejing Lei, Ganning Zhao, Kaitai Zhang +1
An explainable, efficient and lightweight method for texture generation, called TGHop (an acronym of Texture Generation PixelHop), is proposed in this work. Although synthesis of v…
Evaluation of Multimodal Semantic Segmentation using RGB-D Data
Jiesi Hu, Ganning Zhao, Suya You +1
Our goal is to develop stable, accurate, and robust semantic scene understanding methods for wide-area scene perception and understanding, especially in challenging outdoor environ…
CalibDNN: Multimodal Sensor Calibration for Perception Using Deep Neural Networks
Ganning Zhao, Jiesi Hu, Suya You +1
Current perception systems often carry multimodal imagers and sensors such as 2D cameras and 3D LiDAR sensors. To fuse and utilize the data for downstream perception tasks, robust…
NITES: A Non-Parametric Interpretable Texture Synthesis Method
Xuejing Lei, Ganning Zhao, C. -C. Jay Kuo
A non-parametric interpretable texture synthesis method, called the NITES method, is proposed in this work. Although automatic synthesis of visually pleasant texture can be achieve…