Open Vocabulary Object Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

7 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 92 papers with code (145 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Open-Vocabulary DETR with Conditional Matching
  22 Mar 2022 4 repositories listed Syntology ran 3 of 8 samples · 5 unverified · 4 pointer-only (licence)
  To this end, we propose a novel open-vocabulary detector based on DETR -- hence the name OV-DETR -- which, once trained, can detect any object given its class name or an exemplar image.
• Open-Vocabulary DETR with Conditional Matching
  22 Mar 2022 4 repositories listed Syntology ran 3 of 8 samples · 5 unverified · 4 pointer-only (licence)
  To this end, we propose a novel open-vocabulary detector based on DETR -- hence the name OV-DETR -- which, once trained, can detect any object given its class name or an exemplar image.
• Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
  28 Apr 2021 4 repositories listed
  On COCO, ViLD outperforms the previous state-of-the-art by 4.
• Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
  28 Apr 2021 4 repositories listed
  On COCO, ViLD outperforms the previous state-of-the-art by 4.
• Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement
  9 Mar 2025 3 repositories listed
  Traditional methods for reasoning segmentation rely on supervised fine-tuning with categorical labels and simple descriptions, limiting its out-of-domain generalization and lacking explicit reasoning processes.
• YOLO-World: Real-Time Open-Vocabulary Object Detection
  30 Jan 2024 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  The You Only Look Once (YOLO) series of detectors have established themselves as efficient and practical tools.
• YOLO-World: Real-Time Open-Vocabulary Object Detection
  30 Jan 2024 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  The You Only Look Once (YOLO) series of detectors have established themselves as efficient and practical tools.
• Scaling Open-Vocabulary Object Detection
  16 Jun 2023 3 repositories listed
  However, with OWL-ST, we can scale to over 1B examples, yielding further large improvement: With an L/14 architecture, OWL-ST improves AP on LVIS rare classes, for which the model has seen no human box annotations, from…
• Scaling Open-Vocabulary Object Detection
  16 Jun 2023 3 repositories listed
  However, with OWL-ST, we can scale to over 1B examples, yielding further large improvement: With an L/14 architecture, OWL-ST improves AP on LVIS rare classes, for which the model has seen no human box annotations, from…
• Unconstrained Open Vocabulary Image Classification: Zero-Shot Transfer from Text to Image via CLIP Inversion
  15 Jul 2024 2 repositories listed
  This effectively inverts the CLIP text encoder and allows textual object labels from essentially the entire English language to be generated directly from image-derived embedding vectors, without requiring any a priori…
• Is CLIP the main roadblock for fine-grained open-world perception?
  4 Apr 2024 2 repositories listed Syntology ran 15 of 17 samples · 2 unverified · 17 pointer-only (licence)
  Modern applications increasingly demand flexible computer vision models that adapt to novel concepts not encountered during training.
• Is CLIP the main roadblock for fine-grained open-world perception?
  4 Apr 2024 2 repositories listed Syntology ran 15 of 17 samples · 2 unverified · 17 pointer-only (licence)
  Modern applications increasingly demand flexible computer vision models that adapt to novel concepts not encountered during training.
• Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head
  11 Mar 2024 2 repositories listed
  End-to-end transformer-based detectors (DETRs) have shown exceptional performance in both closed-set and open-vocabulary object detection (OVD) tasks through the integration of language modalities.
• Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head
  11 Mar 2024 2 repositories listed
  End-to-end transformer-based detectors (DETRs) have shown exceptional performance in both closed-set and open-vocabulary object detection (OVD) tasks through the integration of language modalities.
• Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector
  5 Feb 2024 2 repositories listed Syntology ran 9 of 11 samples · 2 unverified
  This paper studies the challenging cross-domain few-shot object detection (CD-FSOD), aiming to develop an accurate object detector for novel domains with minimal labeled examples.
• Region-centric Image-Language Pretraining for Open-Vocabulary Detection
  29 Sep 2023 2 repositories listed
  We present a new open-vocabulary detection approach based on region-centric image-language pretraining to bridge the gap between image-level pretraining and open-vocabulary object detection.
• Region-centric Image-Language Pretraining for Open-Vocabulary Detection
  29 Sep 2023 2 repositories listed
  We present a new open-vocabulary detection approach based on region-centric image-language pretraining to bridge the gap between image-level pretraining and open-vocabulary object detection.
• Taming Self-Training for Open-Vocabulary Object Detection
  11 Aug 2023 2 repositories listed
  This work identifies two challenges of using self-training in OVD: noisy PLs from VLMs and frequent distribution changes of PLs.
• Taming Self-Training for Open-Vocabulary Object Detection
  11 Aug 2023 2 repositories listed
  This work identifies two challenges of using self-training in OVD: noisy PLs from VLMs and frequent distribution changes of PLs.
• Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers
  11 May 2023 2 repositories listed Syntology ran 5 of 8 samples · 3 unverified
  We present Region-aware Open-vocabulary Vision Transformers (RO-ViT) - a contrastive image-text pretraining recipe to bridge the gap between image-level pretraining and open-vocabulary object detection.
• Region-Aware Pretraining for Open-Vocabulary Object Detection with Vision Transformers
  11 May 2023 2 repositories listed Syntology ran 5 of 8 samples · 3 unverified
  We present Region-aware Open-vocabulary Vision Transformers (RO-ViT) - a contrastive image-text pretraining recipe to bridge the gap between image-level pretraining and open-vocabulary object detection.
• X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion
  7 Dec 2022 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  We demonstrate for the first time that using a text2image model to generate images or zero-shot recognition model to filter noisily crawled images for different object categories is a feasible way to make Copy-Paste…
• PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning
  21 Nov 2022 2 repositories listed Syntology ran 5 of 12 samples · 7 unverified
  In this paper, we first collaborate CLIP and GPT to be a unified 3D open-world learner, named as PointCLIP V2, which fully unleashes their potential for zero-shot 3D classification, segmentation, and detection.
• Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization
  22 Jun 2022 2 repositories listed Syntology ran 7 of 9 samples · 2 unverified
  Open-vocabulary object detection (OVD) aims to scale up vocabulary size to detect objects of novel categories beyond the training vocabulary.
• Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization
  22 Jun 2022 2 repositories listed Syntology ran 7 of 9 samples · 2 unverified
  Open-vocabulary object detection (OVD) aims to scale up vocabulary size to detect objects of novel categories beyond the training vocabulary.
• Simple Open-Vocabulary Object Detection with Vision Transformers
  12 May 2022 2 repositories listed
  Combining simple architectures with large-scale pre-training has led to massive improvements in image classification.
• Simple Open-Vocabulary Object Detection with Vision Transformers
  12 May 2022 2 repositories listed
  Combining simple architectures with large-scale pre-training has led to massive improvements in image classification.
• PointCLIP: Point Cloud Understanding by CLIP
  4 Dec 2021 2 repositories listed
  On top of that, we design an inter-view adapter to better extract the global feature and adaptively fuse the few-shot knowledge learned from 3D into CLIP pre-trained in 2D.
• FG-CLIP: Fine-Grained Visual and Textual Alignment
  8 May 2025 1 repository listed Syntology ran 2 of 2 samples · 0 unverified
  We construct a comprehensive dataset, termed FineHARD, by integrating high-quality region-specific annotations with hard fine-grained negative samples.
• FG-CLIP: Fine-Grained Visual and Textual Alignment
  8 May 2025 1 repository listed Syntology ran 2 of 2 samples · 0 unverified
  We construct a comprehensive dataset, termed FineHARD, by integrating high-quality region-specific annotations with hard fine-grained negative samples.

Syntology lines on 15 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.