6 citations · 9 across the 12 of their papers we have counts for
12 papers · 1 filter
PixelSmile: Toward Fine-Grained Facial Expression Editing
Jiabin Hua, Hengyuan Xu, Aojie Li +4
Fine-grained facial expression editing has long been limited by intrinsic semantic overlap. To address this, we construct the Flex Facial Expression (FFE) dataset with continuous a…
Yume: An Interactive World Generation Model
Xiaofeng Mao, Shaoheng Lin, Zhen Li +7
Yume aims to use images, text, or videos to create an interactive, realistic, and dynamic world, which allows exploration and control using peripheral devices or neural signals. In…
UniCombine: Unified Multi-Conditional Combination with Diffusion Transformer
Haoxuan Wang, Jinlong Peng, Qingdong He +9
With the rapid development of diffusion models in image generation, the demand for more powerful and flexible controllable frameworks is increasing. Although existing methods can g…
PixelPonder: Dynamic Patch Adaptation for Enhanced Multi-Conditional Text-to-Image Generation
Yanjie Pan, Qingdong He, Zhengkai Jiang +9
Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing ControlNet-like methods struggle…
Mamba-YOLO-World: Marrying YOLO-World with Mamba for Open-Vocabulary Detection
Haoxuan Wang, Qingdong He, Jinlong Peng +3
Open-vocabulary detection (OVD) aims to detect objects beyond a predefined set of categories. As a pioneering model incorporating the YOLO series into OVD, YOLO-World is well-suite…
OSV: One Step is Enough for High-Quality Image to Video Generation
Xiaofeng Mao, Zhengkai Jiang, Fu-Yun Wang +5
Video diffusion models have shown great potential in generating high-quality videos, making them an increasingly popular focus. However, their inherent iterative nature leads to su…
MDT-A2G: Exploring Masked Diffusion Transformers for Co-Speech Gesture Generation
Xiaofeng Mao, Zhengkai Jiang, Qilin Wang +7
Recent advancements in the field of Diffusion Transformers have substantially improved the generation of high-quality 2D images, 3D videos, and 3D shapes. However, the effectivenes…
Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation
Ying Jin, Jinlong Peng, Qingdong He +8
The performance of anomaly inspection in industrial manufacturing is constrained by the scarcity of anomaly data. To overcome this challenge, researchers have started employing ano…
AdapNet: Adaptive Noise-Based Network for Low-Quality Image Retrieval
Sihe Zhang, Qingdong He, Jinlong Peng +6
Image retrieval aims to identify visually similar images within a database using a given query image. Traditional methods typically employ both global and local features extracted…
SCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection
Qiangang Du, Jinlong Peng, Xu Chen +4
In recent years, change detection and anomaly detection models based on CNN and transformer have achieved remarkable success across various datasets based on paired data. However,…
Leveraging Fine-Grained Information and Noise Decoupling for Remote Sensing Change Detection
Qiangang Du, Jinlong Peng, Changan Wang +6
Change detection aims to identify remote sense object changes by analyzing data between bitemporal image pairs. Due to the large temporal and spatial span of data collection in cha…
Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection
Liren He, Zhengkai Jiang, Jinlong Peng +7
In the field of multi-class anomaly detection, reconstruction-based methods derived from single-class anomaly detection face the well-known challenge of "learning shortcuts", where…