Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? | Paper Citation Record

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This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 1

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This paper cites YOLO-World: Real-Time Open-Vocabulary Object Detection.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? YOLO-World: Real-Time Open-Vocabulary Object Detection

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This paper cites InProceedings of the IEEE/CVF International Conference on Computer Vision, 1780–1790 (2021).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? InProceedings of the IEEE/CVF International Conference on Computer Vision, 1780–1790 (2021)

Reference 3

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This paper cites Glipv2: Unifying localization and vision-language understanding.Advances in Neural Information Processing Systems35, 36067–36080 (2022).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Glipv2: Unifying localization and vision-language understanding.Advances in Neural Information Processing Systems35, 36067–36080 (2022)

Reference 4

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This paper cites InProceedings of the IEEE/CVF conference on computer vision and pattern recognition, 16793–16803 (2022).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? InProceedings of the IEEE/CVF conference on computer vision and pattern recognition, 16793–16803 (2022)

Reference 5

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This paper cites In Proceedings of the IEEE/CVF International Conference on Computer Vision, 6339–6350 (2023).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? In Proceedings of the IEEE/CVF International Conference on Computer Vision, 6339–6350 (2023)

Reference 6

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This paper cites A simple framework for open-vocabulary segmentation and detection.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? A simple framework for open-vocabulary segmentation and detection

Reference 7

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This paper cites On the Potential of Open-Vocabulary Models for Object Detection in Unusual Street Scenes.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? On the Potential of Open-Vocabulary Models for Object Detection in Unusual Street Scenes

Reference 8

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Sünderhauf, N

Reference 9

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Sünderhauf, N

Reference 10

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This paper cites & Rottmann, M.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Rottmann, M

Reference 11

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Gottschalk, H

Reference 12

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This paper cites VOS: Learning What You Don't Know by Virtual Outlier Synthesis.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? VOS: Learning What You Don't Know by Virtual Outlier Synthesis

Reference 13

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This paper cites & Sünderhauf, N.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Sünderhauf, N

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Unresolved cited work

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 16

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Nguyen, K

Reference 17

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Unresolved cited work

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This paper cites Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head

Reference 19

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This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 20

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This paper cites Lost and found: detecting small road hazards for self-driving vehicles.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Lost and found: detecting small road hazards for self-driving vehicles

Reference 21

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Unresolved cited work

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This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Ommer, B

Reference 24

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Zhang, K

Reference 26

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Repaint: Inpainting using denoising diffusion probabilistic models

Reference 27

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Martinez, A

Reference 28

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Yang, W

Reference 29

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This paper cites Stable Diffusion Web UI (2022).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Stable Diffusion Web UI (2022)

Reference 30

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? ImagenHub: Standardizing the evaluation of conditional image generation models

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This paper cites Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images

Reference 32

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Tang, Y

Reference 33

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This paper cites How much real data do we actually need: Analyzing object detection performance using synthetic and real data.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? How much real data do we actually need: Analyzing object detection performance using synthetic and real data

Reference 34

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Zhao, R

Reference 35

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Can OOD Object Detectors Learn from Foundation Models?

Reference 37

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Cadena, C

Reference 38

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Cord, M

Reference 39

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This paper cites In 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 182–189 (IEEE, 2021).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? In 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 182–189 (IEEE, 2021)

Reference 40

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Unresolved cited work

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This paper cites InComputer vision–ECCV 2014: 13th Eu- ropean conference, zurich, Switzerland, September 6-12, 2014, proceedings, part v 13, 740–755 (Springer, 2014).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? InComputer vision–ECCV 2014: 13th Eu- ropean conference, zurich, Switzerland, September 6-12, 2014, proceedings, part v 13, 740–755 (Springer, 2014)

Reference 43

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Girshick, R

Reference 44

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Unresolved cited work

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Falchi, F

Reference 46

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This paper cites Dreamshaper (revision 8c1bfc6) (2023).

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Dreamshaper (revision 8c1bfc6) (2023)

Reference 47

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This paper cites Stable Diffusion Inpainting.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Stable Diffusion Inpainting

Reference 48

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This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 49

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Swin transformer: Hierarchical vision transformer using shifted windows

Reference 50

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 51

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? You only look once: Unified, real-time object detection

Reference 52

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Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? & Qiu, J

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:36:19.027452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 29ae174e-5e6d-4862-9af4-e1807b3583f6 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Learning transferable visual models from natural language supervision

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:36:19.017053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4367e64b-8a1a-4b77-83c1-efbc75fabb28 · outbound

This paper cites End-to-end object detection with transformers.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? End-to-end object detection with transformers

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:36:19.005713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d57a1505-2b3e-41cd-bb85-8d3eedc3d333 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:18.706367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26a51f06-ae8e-4e81-8948-023bd30e66ef · outbound

This paper cites DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:18.709505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab22c0ad-749c-46da-a690-68b553b9401a · outbound

This paper cites Denoising Diffusion Implicit Models.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? Denoising Diffusion Implicit Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:18.712859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c620061b-803e-4e43-8dc3-5c3f49360751 · outbound

This paper cites object in the street.

Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? object in the street

Reference 59

Resolution: verified exact; raw_fallback, observed 2026-08-06T21:36:18.817206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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