mlsanityData to 14 Oct 2026

Visual Recognition by Request

arXiv 2207.14227 ↗First posted 28 Jul 2022cs.CVcited by 10

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Abstract (arXiv)

Humans have the ability of recognizing visual semantics in an unlimited granularity, but existing visual recognition algorithms cannot achieve this goal. In this paper, we establish a new paradigm named visual recognition by request (ViRReq) to bridge the gap. The key lies in decomposing visual recognition into atomic tasks named requests and leveraging a knowledge base, a hierarchical and text-based dictionary, to assist task definition. ViRReq allows for (i) learning complicated whole-part hierarchies from highly incomplete annotations and (ii) inserting new concepts with minimal efforts. We also establish a solid baseline by integrating language-driven recognition into recent semantic and instance segmentation methods, and demonstrate its flexible recognition ability on CPP and ADE20K, two datasets with hierarchical whole-part annotations.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 62 of its 85 references that are in the map. First posted on arXiv 28 Jul 2022.

Builds on

62 of 85 references.

References · 62

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38 more
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50 most cited of 62 All 62 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 4; 2025: 2; 2026: 1.

10 papers.

  1. 2025VisRL: Intention-Driven Visual Perception via Reinforced Reasoningcited by 39
  2. 2023OV-PARTS: Towards Open-Vocabulary Part Segmentationcited by 31
  3. 2025CAPability: A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughnesscited by 25
  4. 2023PanopticPartFormer++: A Unified and Decoupled View for Panoptic Part Segmentationcited by 19
  5. 2024PartGLEE: A Foundation Model for Recognizing and Parsing Any Objectscited by 15
  6. 2024SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentationcited by 6
  7. 2023Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Modelscited by 5
  8. 2024Task-aligned Part-aware Panoptic Segmentation through Joint Object-Part Representationscited by 5
  9. 2024SPIN: Hierarchical Segmentation with Subpart Granularity in Natural Imagescited by 5
  10. 2026COCOTree: A Dataset and Benchmark for Open Tree-Structured Visual Decompositioncited by 0