View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network
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Abstract (arXiv)
This paper describes the details of Sighthound's fully automated vehicle make, model and color recognition system. The backbone of our system is a deep convolutional neural network that is not only computationally inexpensive, but also provides state-of-the-art results on several competitive benchmarks. Additionally, our deep network is trained on a large dataset of several million images which are labeled through a semi-automated process. Finally we test our system on several public datasets as well as our own internal test dataset. Our results show that we outperform other methods on all benchmarks by significant margins. Our model is available to developers through the Sighthound Cloud API at https://www.sighthound.com/products/cloud
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Feb 2017.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 5; 2025: 2; 2026: 1.
9 papers.
- 2024Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Modelscited by 15
- 2024HEX: Hierarchical Emergence Exploitation in Self-Supervised Algorithmscited by 7
- 2024Superpixel Tokenization for Vision Transformers: Preserving Semantic Integrity in Visual Tokenscited by 6
- 2024Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Visioncited by 5
- 2025ForAug: Mitigating Biases in Image Classification via Controlled Image Compositionscited by 2
- 2025All You Need to Know About Training Image Retrieval Modelscited by 1
- 2021Real-time smart vehicle surveillance systemcited by 0
- 2024Adaptive Prompt Tuning: Vision Guided Prompt Tuning with Cross-Attention for Fine-Grained Few-Shot Learningcited by 0
- 2026Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregationcited by 0
- 2026Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation16 Jun 2026
- 2025All You Need to Know About Training Image Retrieval Models17 Mar 2025
- 2025ForAug: Mitigating Biases in Image Classification via Controlled Image Compositions12 Mar 2025
- 2024Adaptive Prompt Tuning: Vision Guided Prompt Tuning with Cross-Attention for Fine-Grained Few-Shot Learning19 Dec 2024
- 2024Superpixel Tokenization for Vision Transformers: Preserving Semantic Integrity in Visual Tokens6 Dec 2024
- 2024HEX: Hierarchical Emergence Exploitation in Self-Supervised Algorithms30 Oct 2024
- 2024Advancing Cross-domain Discriminability in Continual Learning of Vision-Language Models27 Jun 2024
- 2024Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision9 Jun 2024
- 2021Real-time smart vehicle surveillance system24 Nov 2021