Landmark Retrieval

Landmark retrieval focuses on efficiently and accurately searching for specific landmarks (e.g., buildings, monuments) within large image or video datasets. Current research emphasizes improving both the speed and accuracy of retrieval, often employing Siamese networks, vision transformers, and multi-teacher distillation frameworks to learn effective feature representations, sometimes combining global and local image features for enhanced performance. These advancements are crucial for applications like visual localization in robotics and augmented reality, as well as improving the efficiency of large-scale image search engines.