2 citations · 3 across the 6 of their papers we have counts for
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Adaptive Begin-of-Video Tokens for Autoregressive Video Diffusion Models
Tianle Cheng, Zeyan Zhang, Kaifeng Gao +1
Recent advancements in diffusion-based video generation have produced impressive and high-fidelity short videos. To extend these successes to generate coherent long videos, most vi…
OCCO: LVM-guided Infrared and Visible Image Fusion Framework based on Object-aware and Contextual COntrastive Learning
Hui Li, Congcong Bian, Zeyang Zhang +3
Image fusion is a crucial technique in the field of computer vision, and its goal is to generate high-quality fused images and improve the performance of downstream tasks. However,…
One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusion
Chunyang Cheng, Tianyang Xu, Zhenhua Feng +7
Advanced image fusion methods mostly prioritise high-level missions, where task interaction struggles with semantic gaps, requiring complex bridging mechanisms. In contrast, we pro…
One Latent Space to Rule All Degradations: Unifying Restoration Knowledge for Image Fusion
Haolong Ma, Hui Li, Chunyang Cheng +4
All-in-One Degradation-Aware Fusion Models (ADFMs) as one of multi-modal image fusion models, which aims to address complex scenes by mitigating degradations from source images and…
CoMoFusion: Fast and High-quality Fusion of Infrared and Visible Image with Consistency Model
Zhiming Meng, Hui Li, Zeyang Zhang +4
Generative models are widely utilized to model the distribution of fused images in the field of infrared and visible image fusion. However, current generative models based fusion m…
BusReF: Infrared-Visible images registration and fusion focus on reconstructible area using one set of features
Zeyang Zhang, Hui Li, Tianyang Xu +2
In a scenario where multi-modal cameras are operating together, the problem of working with non-aligned images cannot be avoided. Yet, existing image fusion algorithms rely heavily…