🤖 Awesome Multi-Agent Collaborative Perception
Explore cutting-edge resources for Multi-Agent Collaborative Perception, Prediction, and Planning
import gradio as gr # Sample data for demonstration perception_papers = [ { "title": "CoSDH: Communication-Efficient Collaborative Perception", "venue": "CVPR 2025", "description": "Novel approach for efficient collaborative perception using supply-demand awareness.", "link": "https://arxiv.org/abs/2503.03430" }, { "title": "V2X-R: Cooperative LiDAR-4D Radar Fusion", "venue": "CVPR 2025", "description": "Cooperative fusion of LiDAR and 4D radar sensors for enhanced 3D object detection.", "link": "https://arxiv.org/abs/2411.08402" }, { "title": "Where2comm: Efficient Collaborative Perception via Spatial Confidence Maps", "venue": "NeurIPS 2022", "description": "Groundbreaking work on efficient collaborative perception using spatial confidence maps.", "link": "https://openreview.net/forum?id=dLL4KXzKUpS" } ] datasets_data = [ ["DAIR-V2X", "2022", "Real-world", "V2I", "71K frames", "3D boxes, Infrastructure"], ["V2V4Real", "2023", "Real-world", "V2V", "20K frames", "Real V2V, Highway"], ["OPV2V", "2022", "Simulation", "V2V", "Large-scale", "CARLA, Multi-agent"], ["V2X-Sim", "2021", "Simulation", "Multi", "Scalable", "Multi-agent, Collaborative"] ] def create_paper_card(paper): return f"""
""" # Custom CSS custom_css = """ .gradio-container { max-width: 1200px !important; } .main-header { text-align: center; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 40px 20px; border-radius: 15px; margin-bottom: 30px; } .stats-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 20px; margin: 20px 0; } .stat-card { background: rgba(255,255,255,0.1); padding: 20px; border-radius: 10px; text-align: center; } """ # Create the interface with gr.Blocks( title="🤖 Awesome Multi-Agent Collaborative Perception", theme=gr.themes.Soft(), css=custom_css ) as demo: # Header gr.HTML("""Explore cutting-edge resources for Multi-Agent Collaborative Perception, Prediction, and Planning
We welcome contributions! Please submit papers, datasets, and code repositories via GitHub.