Learning 1-Bit LiDAR-based Localization with Auxiliary Objective

arXiv:2606.27729 · cs.CV · Submitted 2026-06-26 · Read on arXiv

cs.CV

Submitted: 2026-06-26

Updated: 2026-09-22

Comments: European Conference on Computer Vision(ECCV)

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Distillation — 20× in this paper · explained in 2 episodes
• Transformer — 12× in this paper · explained in 2 episodes
• Quantization — 10× in this paper · explained in 12 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Knowledge Distillation — 5× in this paper · explained in 11 episodes
• alpha — 5× in this paper · explained in 1 episode
• Optimal Transport — 4× in this paper · explained in 5 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Loss Function — 3× in this paper · explained in 2 episodes
• Pruning — 3× in this paper · explained in 4 episodes
• Absolute Pose Regression — 2× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Point Clouds — 2× in this paper · explained in 2 episodes
• Redundancy — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation Studies — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Scene Coordinate Regression — 1× in this paper
• Self-distillation — 1× in this paper · explained in 6 episodes
• Straight-Through Estimator — 1× in this paper
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
• cuDNN: Efficient Primitives for Deep Learning
• Distilling the Knowledge in a Neural Network
• DINOv2: Learning Robust Visual Features without Supervision
• Opening the Black Box of Deep Neural Networks via Information
• The information bottleneck method

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