31 citations · 43 across the 17 of their papers we have counts for
18 papers
EvTexture++: Event-Driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang +1
Event-based vision has drawn increasing attention owing to its distinctive properties, including ultra-high temporal resolution and extreme dynamic range. Recent works have introdu…
Seeing the Unseen: Zooming in the Dark with Event Cameras
Dachun Kai, Zeyu Xiao, Huyue Zhu +3
This paper addresses low-light video super-resolution (LVSR), aiming to restore high-resolution videos from low-light, low-resolution (LR) inputs. Existing LVSR methods often strug…
Efficient Event-Based Semantic Segmentation via Exploiting Frame-Event Fusion: A Hybrid Neural Network Approach
Hebei Li, Yansong Peng, Jiahui Yuan +4
Event cameras have recently been introduced into image semantic segmentation, owing to their high temporal resolution and other advantageous properties. However, existing event-bas…
Create Anything Anywhere: Layout-Controllable Personalized Diffusion Model for Multiple Subjects
Wei Li, Hebei Li, Yansong Peng +3
Diffusion models have significantly advanced text-to-image generation, laying the foundation for the development of personalized generative frameworks. However, existing methods la…
Event-Enhanced Blurry Video Super-Resolution
Dachun Kai, Yueyi Zhang, Jin Wang +3
In this paper, we tackle the task of blurry video super-resolution (BVSR), aiming to generate high-resolution (HR) videos from low-resolution (LR) and blurry inputs. Current BVSR m…
Spiking Point Transformer for Point Cloud Classification
Peixi Wu, Bosong Chai, Hebei Li +6
Spiking Neural Networks (SNNs) offer an attractive and energy-efficient alternative to conventional Artificial Neural Networks (ANNs) due to their sparse binary activation. When SN…
Denoising Designs-inherited Search Framework for Image Denoising
Zheyu Zhang, Yueyi Zhang, Xiaoyan sun
How to benefit from plenty of existing denoising designs? Few methods via Neural Architecture Search (NAS) intend to answer this question. However, these NAS-based denoising method…
D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement
Yansong Peng, Hebei Li, Peixi Wu +3
We introduce D-FINE, a powerful real-time object detector that achieves outstanding localization precision by redefining the bounding box regression task in DETR models. D-FINE com…
Anatomical Consistency Distillation and Inconsistency Synthesis for Brain Tumor Segmentation with Missing Modalities
Zheyu Zhang, Xinzhao Liu, Zheng Chen +4
Multi-modal Magnetic Resonance Imaging (MRI) is imperative for accurate brain tumor segmentation, offering indispensable complementary information. Nonetheless, the absence of moda…
EE-MLLM: A Data-Efficient and Compute-Efficient Multimodal Large Language Model
Feipeng Ma, Yizhou Zhou, Zheyu Zhang +7
Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated satisfactory performance across various vision-language tasks. Current approaches for vision and l…
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang +1
Event-based vision has drawn increasing attention due to its unique characteristics, such as high temporal resolution and high dynamic range. It has been used in video super-resolu…
Visual Perception by Large Language Model's Weights
Feipeng Ma, Hongwei Xue, Guangting Wang +7
Existing Multimodal Large Language Models (MLLMs) follow the paradigm that perceives visual information by aligning visual features with the input space of Large Language Models (L…
Multi-Modal Generative Embedding Model
Feipeng Ma, Hongwei Xue, Guangting Wang +7
Most multi-modal tasks can be formulated into problems of either generation or embedding. Existing models usually tackle these two types of problems by decoupling language modules…
Event-assisted Low-Light Video Object Segmentation
Hebei Li, Jin Wang, Jiahui Yuan +6
In the realm of video object segmentation (VOS), the challenge of operating under low-light conditions persists, resulting in notably degraded image quality and compromised accurac…
Scene Adaptive Sparse Transformer for Event-based Object Detection
Yansong Peng, Hebei Li, Yueyi Zhang +2
While recent Transformer-based approaches have shown impressive performances on event-based object detection tasks, their high computational costs still diminish the low power cons…
Graph Relation Distillation for Efficient Biomedical Instance Segmentation
Xiaoyu Liu, Yueyi Zhang, Zhiwei Xiong +4
Instance-aware embeddings predicted by deep neural networks have revolutionized biomedical instance segmentation, but its resource requirements are substantial. Knowledge distillat…
GET: Group Event Transformer for Event-Based Vision
Yansong Peng, Yueyi Zhang, Zhiwei Xiong +2
Event cameras are a type of novel neuromorphic sen-sor that has been gaining increasing attention. Existing event-based backbones mainly rely on image-based designs to extract spat…
EGVD: Event-Guided Video Deraining
Yueyi Zhang, Jin Wang, Wenming Weng +2
With the rapid development of deep learning, video deraining has experienced significant progress. However, existing video deraining pipelines cannot achieve satisfying performance…