李和倍

李和倍

博士生

Interests
  • 脉冲神经网络
Publications
  1. Facm: Flow-anchored consistency models 2026
  2. RiO-DETR: DETR for Real-time Oriented Object Detection 2026
  3. Dome-DETR: DETR with density-oriented feature-query manipulation for efficient tiny object detection 2025
  4. Dash: 4d hash encoding with self-supervised decomposition for real-time dynamic scene rendering 2025
  5. Efficient spiking point mamba for point cloud analysis 2025
  6. Enhancing Visual Question Answering Via Clustered In-Context Sequence Configuration 2025
  7. Create anything anywhere: Layout-controllable personalized diffusion model for multiple subjects 2025
  8. D-FINE: Redefine regression task of DETRs as fine-grained distribution refinement 2025
  9. Efficient event-based semantic segmentation via exploiting frame-event fusion: A hybrid neural network approach 2025
  10. Spiking point transformer for point cloud classification 2025
  11. Enhancing Visual Tracking by Leveraging High-frequency Information within Event Signals 2025
  12. Event-based head pose estimation: Benchmark and method 2024
  13. Ee-mllm: A data-efficient and compute-efficient multimodal large language model 2024
  14. Event-assisted low-light video object segmentation 2024
  15. Scene adaptive sparse transformer for event-based object detection 2024
  16. Deep multi-threshold spiking-UNet for image processing 2024
  17. Eoformer: Edge-oriented transformer for brain tumor segmentation 2023
  18. Deep spiking-unet for image processing 2023
  19. Dual progressive prototype network for generalized zero-shot learning 2021
  20. Task-independent knowledge makes for transferable representations for generalized zero-shot learning 2021