9 papers · 1 filter
Traffic-CBM: A Structurally Interpretable Multimodal Framework for Encrypted Traffic Classification
Honglei Jin, Wenshuo Chen, Shaofeng Liang +6
Encrypted traffic classification has achieved strong performance, but its decision process remains difficult to interpret. Existing methods usually combine flow statistics, packet…
MemoGen: Can Past Experience Improve Future Text-to-Image Generation?
Wenshuo Chen, Kuimou Yu, Bowen Tian +10
Modern text-to-image models have achieved strong visual synthesis, yet remain unreliable when prompts require implicit visual constraints, relational reasoning, or external knowled…
Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models
Haosen Li, Wenshuo Chen, Lei Wang +4
Diffusion models have achieved remarkable success in synthesizing complex static and temporal visuals, a breakthrough largely driven by Classifier-Free Guidance (CFG). However, des…
Oracle Noise: Faster Semantic Spherical Alignment for Interpretable Latent Optimization
Haosen Li, Wenshuo Chen, Lei Wang +3
Text-to-image diffusion models have achieved remarkable generative capabilities, yet accurately aligning complex textual prompts with synthesized layouts remains an ongoing challen…
-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models
Haosen Li, Wenshuo Chen, Shaofeng Liang +3
Diffusion models have achieved unprecedented success in text-aligned generation, largely driven by Classifier-Free Guidance (CFG). However, standard CFG operates strictly on instan…
ECHO: Edge-Cloud Humanoid Orchestration for Language-to-Motion Control
Haozhe Jia, Jianfei Song, Yuan Zhang +5
We present ECHO, an edge--cloud framework for language-driven whole-body control of humanoid robots. A cloud-hosted diffusion-based text-to-motion generator synthesizes motion refe…
Neural Electromagnetic Fields for High-Resolution Material Parameter Reconstruction
Zhe Chen, Peilin Zheng, Wenshuo Chen +3
Creating functional Digital Twins, simulatable 3D replicas of the real world, is a central challenge in computer vision. Current methods like NeRF produce visually rich but functio…
CoEmoGen: Towards Semantically-Coherent and Scalable Emotional Image Content Generation
Kaishen Yuan, Yuting Zhang, Shang Gao +3
Emotional Image Content Generation (EICG) aims to generate semantically clear and emotionally faithful images based on given emotion categories, with broad application prospects. W…
Physics-Informed Representation Alignment for Sparse Radio-Map Reconstruction
Haozhe Jia, Wenshuo Chen, Zhihui Huang +7
Radio map reconstruction is essential for enabling advanced applications, yet challenges such as complex signal propagation and sparse observational data hinder accurate reconstruc…