mlsanityData to 13 Oct 2026

A Fast and Accurate One-Stage Approach to Visual Grounding

arXiv 1908.06354 ↗First posted 18 Aug 2019cs.CVcited by 194

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Abstract (arXiv)

We propose a simple, fast, and accurate one-stage approach to visual grounding, inspired by the following insight. The performances of existing propose-and-rank two-stage methods are capped by the quality of the region candidates they propose in the first stage --- if none of the candidates could cover the ground truth region, there is no hope in the second stage to rank the right region to the top. To avoid this caveat, we propose a one-stage model that enables end-to-end joint optimization. The main idea is as straightforward as fusing a text query's embedding into the YOLOv3 object detector, augmented by spatial features so as to account for spatial mentions in the query. Despite being simple, this one-stage approach shows great potential in terms of both accuracy and speed for both phrase localization and referring expression comprehension, according to our experiments. Given these results along with careful investigations into some popular region proposals, we advocate for visual grounding a paradigm shift from the conventional two-stage methods to the one-stage framework.

Key facts. Cited by 194 papers in the map (data through 13 Oct 2026). First posted on arXiv 18 Aug 2019.

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Cited by year (2026 to 13 Oct)

Citing papers per year: 2021: 31; 2022: 48; 2023: 53; 2024: 32; 2025: 24; 2026: 6.

194 papers.

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  1. 2021MDETR -- Modulated Detection for End-to-End Multi-Modal Understandingcited by 815
  2. 2021TransVG: End-to-End Visual Grounding with Transformerscited by 269
  3. 2023GRES: Generalized Referring Expression Segmentationcited by 254
  4. 2023Universal Instance Perception as Object Discovery and Retrievalcited by 191
  5. 2024EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domaincited by 181
  6. 2023PolyFormer: Referring Image Segmentation as Sequential Polygon Generationcited by 147
  7. 2021Referring Transformer: A One-step Approach to Multi-task Visual Groundingcited by 143
  8. 2023Multi3DRefer: Grounding Text Description to Multiple 3D Objectscited by 142
  9. 2021InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referringcited by 140
  10. 2022SeqTR: A Simple yet Universal Network for Visual Groundingcited by 138
  11. 2023GPT-4V in Wonderland: Large Multimodal Models for Zero-Shot Smartphone GUI Navigationcited by 137
  12. 2021Bottom Up Top Down Detection Transformers for Language Grounding in Images and Point Cloudscited by 128
38 more
  1. 2021Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmarkcited by 124
  2. 2021SAT: 2D Semantics Assisted Training for 3D Visual Groundingcited by 124
  3. 2021UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language Modelingcited by 122
  4. 2022RSVG: Exploring Data and Models for Visual Grounding on Remote Sensing Datacited by 121
  5. 2022Vision-Language Pre-training: Basics, Recent Advances, and Future Trendscited by 117
  6. 2024SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Modelcited by 112
  7. 2021Encoder Fusion Network with Co-Attention Embedding for Referring Image Segmentationcited by 111
  8. 2022VLT: Vision-Language Transformer and Query Generation for Referring Segmentationcited by 110
  9. 20223D-SPS: Single-Stage 3D Visual Grounding via Referred Point Progressive Selectioncited by 109
  10. 2022TubeDETR: Spatio-Temporal Video Grounding with Transformerscited by 98
  11. 2023Vision-Language Models in Remote Sensing: Current Progress and Future Trendscited by 93
  12. 2021TransRefer3D: Entity-and-Relation Aware Transformer for Fine-Grained 3D Visual Groundingcited by 86
  13. 2023Open-vocabulary Object Segmentation with Diffusion Modelscited by 82
  14. 2021Free-form Description Guided 3D Visual Graph Network for Object Grounding in Point Cloudcited by 81
  15. 2023Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentationcited by 76
  16. 2022Multi-Modal Knowledge Graph Construction and Application: A Surveycited by 74
  17. 2023ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding with GPT and Prototype Guidancecited by 70
  18. 2022Improving Visual Grounding with Visual-Linguistic Verification and Iterative Reasoningcited by 69
  19. 2023Joint Visual Grounding and Tracking with Natural Language Specificationcited by 59
  20. 2022Shifting More Attention to Visual Backbone: Query-modulated Refinement Networks for End-to-End Visual Groundingcited by 52
  21. 2024Toward Visual Grounding: A Surveycited by 52
  22. 2021Look Before You Leap: Learning Landmark Features for One-Stage Visual Groundingcited by 51
  23. 2022Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completioncited by 44
  24. 2021Visual Grounding with Transformerscited by 42
  25. 2022Local-Global Context Aware Transformer for Language-Guided Video Segmentationcited by 41
  26. 2022X-DETR: A Versatile Architecture for Instance-wise Vision-Language Taskscited by 41
  27. 2022TransVG++: End-to-End Visual Grounding with Language Conditioned Vision Transformercited by 41
  28. 2022Embracing Consistency: A One-Stage Approach for Spatio-Temporal Video Groundingcited by 41
  29. 2022Look Around and Refer: 2D Synthetic Semantics Knowledge Distillation for 3D Visual Groundingcited by 41
  30. 2023GREC: Generalized Referring Expression Comprehensioncited by 41
  31. 2023Multi-Modal Mutual Attention and Iterative Interaction for Referring Image Segmentationcited by 36
  32. 2024SimVG: A Simple Framework for Visual Grounding with Decoupled Multi-modal Fusioncited by 36
  33. 2023Language Adaptive Weight Generation for Multi-task Visual Groundingcited by 35
  34. 2021Refer-it-in-RGBD: A Bottom-up Approach for 3D Visual Grounding in RGBD Imagescited by 33
  35. 2021YouRefIt: Embodied Reference Understanding with Language and Gesturecited by 33
  36. 2022Pseudo-Q: Generating Pseudo Language Queries for Visual Groundingcited by 33
  37. 2022ScanEnts3D: Exploiting Phrase-to-3D-Object Correspondences for Improved Visio-Linguistic Models in 3D Scenescited by 32
  38. 2023Medical Phrase Grounding with Region-Phrase Context Contrastive Alignmentcited by 32

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