Desc++: Efficient Descriptor Enhancement for Data Association in Existing Visual SLAM Systems

arXiv:2607.11099 · cs.RO, cs.CV · Submitted 2026-07-13 · Read on arXiv

cs.RO, cs.CV

Submitted: 2026-07-13

Updated: 2026-09-20

Code: https://github.com/ouotingwei/DescPP

Terminology

• Accuracy — 30× in this paper · explained in 1 episode
• Benchmark — 18× in this paper · explained in 2 episodes
• Aggregation — 15× in this paper · explained in 1 episode
• Transformer — 11× in this paper · explained in 2 episodes
• Robustness — 8× in this paper · explained in 5 episodes
• Feature Extraction — 5× in this paper · explained in 2 episodes
• Attention Mechanism — 4× in this paper · explained in 3 episodes
• Computational overhead — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Quantization — 3× in this paper · explained in 12 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Aggregation Architectures — 2× in this paper · explained in 1 episode
• Average Precision — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Learnable Fourier Features — 2× in this paper
• Ablation study — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Hamming Distance — 1× in this paper · explained in 2 episodes
• Hybrid Architectures — 1× in this paper · explained in 3 episodes
• Hybrid Models — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Mean Matching Accuracy — 1× in this paper
• Multi-Layer Perceptron — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Root Mean Square Error — 1× in this paper
• State Space Models (SSMs) — 1× in this paper · explained in 4 episodes
• Two-Stage Architecture — 1× in this paper · explained in 2 episodes

Sources

• An Attention Free Transformer
• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• Decoupled Weight Decay Regularization

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