SHOP-VRB：物体知覚のための視覚推論ベンチマーク
SHOP-VRB: A Visual Reasoning Benchmark for Object Perception
ロボットによる小型物体の把持・操作を対象に、視覚と言語から物体の性質を推論するベンチマークと、記号プログラム実行に基づく推論手法を提案した論文。
著者: Michal Nazarczuk, Krystian Mikolajczyk
分類: cs.CV, cs.AI, cs.LG, cs.RO
原文アブストラクト
In this paper we present an approach and a benchmark for visual reasoning in robotics applications, in particular small object grasping and manipulation. The approach and benchmark are focused on inferring object properties from visual and text data. It concerns small household objects with their properties, functionality, natural language descriptions as well as question-answer pairs for visual reasoning queries along with their corresponding scene semantic representations. We also present a method for generating synthetic data which allows to extend the benchmark to other objects or scenes and propose an evaluation protocol that is more challenging than in the existing datasets. We propose a reasoning system based on symbolic program execution. A disentangled representation of the visual and textual inputs is obtained and used to execute symbolic programs that represent a 'reasoning process' of the algorithm. We perform a set of experiments on the proposed benchmark and compare to results for the state of the art methods. These results expose the shortcomings of the existing benchmarks that may lead to misleading conclusions on the actual performance of the visual reasoning systems.
