6 papers
CEIDM: A Controlled Entity and Interaction Diffusion Model for Enhanced Text-to-Image Generation
Mingyue Yang, Dianxi Shi, Jialu Zhou +4
In Text-to-Image (T2I) generation, the complexity of entities and their intricate interactions pose a significant challenge for T2I method based on diffusion model: how to effectiv…
Dynamic Embedding of Hierarchical Visual Features for Efficient Vision-Language Fine-Tuning
Xinyu Wei, Guoli Yang, Jialu Zhou +4
Large Vision-Language Models (LVLMs) commonly follow a paradigm that projects visual features and then concatenates them with text tokens to form a unified sequence input for Large…
Separation and Collaboration: Two-Level Routing Grouped Mixture-of-Experts for Multi-Domain Continual Learning
Jialu Zhou, Dianxi Shi, Shaowu Yang +5
Multi-Domain Continual Learning (MDCL) acquires knowledge from sequential tasks with shifting class sets and distribution. Despite the Parameter-Efficient Fine-Tuning (PEFT) method…
UniCT Depth: Event-Image Fusion Based Monocular Depth Estimation with Convolution-Compensated ViT Dual SA Block
Luoxi Jing, Dianxi Shi, Zhe Liu +5
Depth estimation plays a crucial role in 3D scene understanding and is extensively used in a wide range of vision tasks. Image-based methods struggle in challenging scenarios, whil…
D3HRL: A Distributed Hierarchical Reinforcement Learning Approach Based on Causal Discovery and Spurious Correlation Detection
Chenran Zhao, Dianxi Shi, Mengzhu Wang +5
Current Hierarchical Reinforcement Learning (HRL) algorithms excel in long-horizon sequential decision-making tasks but still face two challenges: delay effects and spurious correl…
Pairwise Similarity Regularization for Semi-supervised Graph Medical Image Segmentation
Jialu Zhou, Dianxi Shi, Shaowu Yang +3
With fully leveraging the value of unlabeled data, semi-supervised medical image segmentation algorithms significantly reduces the limitation of limited labeled data, achieving a s…