mlsanityData to 7 Oct 2026

Compositional Zero-Shot Learning for Attribute-Based Object Reference in Human-Robot Interaction

arXiv 2312.13655 ↗First posted 21 Dec 2023cs.RO cs.AI cs.CLcited by 0

Not on the map. Why?

Abstract (arXiv)

Language-enabled robots have been widely studied over the past years to enable natural human-robot interaction and teaming in various real-world applications. Language-enabled robots must be able to comprehend referring expressions to identify a particular object from visual perception using a set of referring attributes extracted from natural language. However, visual observations of an object may not be available when it is referred to, and the number of objects and attributes may also be unbounded in open worlds. To address the challenges, we implement an attribute-based compositional zero-shot learning method that uses a list of attributes to perform referring expression comprehension in open worlds. We evaluate the approach on two datasets including the MIT-States and the Clothing 16K. The preliminary experimental results show that our implemented approach allows a robot to correctly identify the objects referred to by human commands.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 22 references that are in the map. First posted on arXiv 21 Dec 2023.

Builds on

10 of 22 references.

References · 10

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  4. 2021Open World Compositional Zero-Shot Learningcited by 100
  5. 2020Symmetry and Group in Attribute-Object Compositionscited by 89
  6. 2022Disentangling Visual Embeddings for Attributes and Objectscited by 55
  7. 2021Learning Graph Embeddings for Open World Compositional Zero-Shot Learningcited by 49
  8. 2023Learning Attention as Disentangler for Compositional Zero-shot Learningcited by 29
  9. 2022Learning Invariant Visual Representations for Compositional Zero-Shot Learningcited by 24
  10. 2021Relation-aware Compositional Zero-shot Learning for Attribute-Object Pair Recognitioncited by 19

Built on by

Not cited yet.