TCFormer: A 5M-Parameter Transformer with Density-Guided Aggregation for Weakly-Supervised Crowd Counting
Analysis
This article introduces TCFormer, a novel transformer model designed for weakly-supervised crowd counting. The key innovation appears to be the density-guided aggregation method, which likely improves performance by focusing on relevant image regions. The use of a relatively small 5M parameter count suggests a focus on efficiency and potentially faster inference compared to larger models. The source being ArXiv indicates this is a research paper, likely detailing the model's architecture, training process, and experimental results.
Key Takeaways
- •TCFormer is a new transformer model for weakly-supervised crowd counting.
- •It uses a density-guided aggregation method.
- •The model has a relatively small 5M parameter count, suggesting efficiency.
- •The paper is likely a research publication on ArXiv.
Reference
“The article likely details the model's architecture, training process, and experimental results.”