3 citations · 3 across the 13 of their papers we have counts for
14 papers
Paris 2.0: A Decentralized Diffusion Model for Video Generation
Ali Rouzbayani, Bidhan Roy, Marcos Villagra +1
We present Paris 2.0, the first video generation model pre-trained through decentralized computation. Its training recipe builds upon Paris 1.0 (arXiv:2510.03434), the first ever o…
DRFusion: Drift-Resilient Temporally Consistent Infrared-Visible Video Fusion
Xingyuan Li, Haoyuan Xu, Shulin Li +3
Infrared and visible video fusion is essential for achieving comprehensive perception in dynamic scenes. However, maintaining temporal consistency remains a formidable challenge. C…
Uncertainty-aware Spatial-Frequency Registration and Fusion for Infrared and Visible Images
Xingyuan Li, Haoyuan Xu, Xingyue Zhu +4
Infrared and Visible Image Fusion (IVIF) has shown promise in visual tasks under challenging environments, but fusion under unregistered conditions faces inherent misalignments. Cu…
UniFusion: A Unified Image Fusion Framework with Robust Representation and Source-Aware Preservation
Xingyuan Li, Songcheng Du, Yang Zou +3
Image fusion aims to integrate complementary information from multiple source images to produce a more informative and visually consistent representation, benefiting both human per…
Toward Real-world Infrared Image Super-Resolution: A Unified Autoregressive Framework and Benchmark Dataset
Yang Zou, Jun Ma, Zhidong Jiao +3
Infrared image super-resolution (IISR) under real-world conditions is a practically significant yet rarely addressed task. Pioneering works are often trained and evaluated on simul…
Bridging Human Evaluation to Infrared and Visible Image Fusion
Jinyuan Liu, Xingyuan Li, Qingyun Mei +5
Infrared and visible image fusion (IVIF) integrates complementary modalities to enhance scene perception. Current methods predominantly focus on optimizing handcrafted losses and o…
Heterogeneous Decentralized Diffusion Models
Zhiying Jiang, Raihan Seraj, Marcos Villagra +1
Training frontier-scale diffusion models often requires substantial computational resources concentrated in tightly-coupled clusters, limiting participation to well-resourced insti…
HATIR: Heat-Aware Diffusion for Turbulent Infrared Video Super-Resolution
Yang Zou, Xingyue Zhu, Kaiqi Han +4
Infrared video has been of great interest in visual tasks under challenging environments, but often suffers from severe atmospheric turbulence and compression degradation. Existing…
CrossRay3D: Geometry and Distribution Guidance for Efficient Multimodal 3D Detection
Huiming Yang, Wenzhuo Liu, Yicheng Qiao +8
The sparse cross-modality detector offers more advantages than its counterpart, the Bird's-Eye-View (BEV) detector, particularly in terms of adaptability for downstream tasks and c…
Depth-Supervised Fusion Network for Seamless-Free Image Stitching
Zhiying Jiang, Ruhao Yan, Zengxi Zhang +2
Image stitching synthesizes images captured from multiple perspectives into a single image with a broader field of view. The significant variations in object depth often lead to la…
DCEvo: Discriminative Cross-Dimensional Evolutionary Learning for Infrared and Visible Image Fusion
Jinyuan Liu, Bowei Zhang, Qingyun Mei +6
Infrared and visible image fusion integrates information from distinct spectral bands to enhance image quality by leveraging the strengths and mitigating the limitations of each mo…
DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-Resolution
Xingyuan Li, Zirui Wang, Yang Zou +5
Infrared imaging is essential for autonomous driving and robotic operations as a supportive modality due to its reliable performance in challenging environments. Despite its popula…
Infrared and Visible Image Fusion: From Data Compatibility to Task Adaption
Jinyuan Liu, Guanyao Wu, Zhu Liu +6
Infrared-visible image fusion (IVIF) is a critical task in computer vision, aimed at integrating the unique features of both infrared and visible spectra into a unified representat…
SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement
Zeru Shi, Zengxi Zhang, Kemeng Cui +3
Images captured in harsh environments often exhibit blurred details, reduced contrast, and color distortion, which hinder feature detection and matching, thereby affecting the accu…