arXiv AI July 10, 2026 By ZhiXin Sun

VocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval

arXiv:2607. 08541v1 Announce Type: cross Abstract: Open-vocabulary object detection and segmentation aim to recognize arbitrary objects beyond predefined categories.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 19

QueryGaussian: Scalable and Training-Free Open-Vocabulary 3D Instance Retrieval

arXiv:2606. 19733v1 Announce Type: cross Abstract: Efficiently retrieving specific 3D instances from large-scale scenes via natural language prompts remains a formidable challenge in multimedia analysis.

By Xiuyuan Zhu, Ke Lu, Zijie Yang, Chao Yue, Jian Xue, Dongming Zhang

rag computer-vision efficiency benchmarks

arXiv AI

6d ago

CORE-3D: Context-aware Open-vocabulary Retrieval by Embeddings in 3D

arXiv:2509. 24528v4 Announce Type: replace-cross Abstract: Object retrieval from a scene has become a new trend of research due to its numerous applications.

By Mohamad Amin Mirzaei, Pantea Amoie, Ali Ekhterachian, Matin Mirzababaei, Babak Khalaj

llms rag computer-vision multimodal benchmarks

arXiv Machine Learning

Jul 3

COVTrack++: Learning Open-Vocabulary Multi-Object Tracking from Continuous Videos via a Synergistic Paradigm

arXiv:2603. 24016v2 Announce Type: replace-cross Abstract: Multi-Object Tracking (MOT) has traditionally focused on a few specific categories, restricting its applicability to real-world scenarios involving diverse objects.

By Zekun Qian, Wei Feng, Ruize Han, Junhui Hou

benchmarks

arXiv AI

Jun 19

Mitigating Simplicity Bias in OOD Detection through Object Co-occurrence Analysis

arXiv:2605. 07821v2 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection is crucial for ensuring the reliability of deep learning models.

By Boyang Dai, Chaoqi Chen, Yizhou Yu

safety

arXiv Machine Learning

Jun 24

Open-Vocabulary BEV Segmentation with 3D-Aware Geometric Constraints

arXiv:2606. 24353v1 Announce Type: cross Abstract: Bird's-eye view (BEV) perception fuses multi-camera images into a unified top-down representation for autonomous driving.

By Hojun Choi, Seulbin Hwang, Dae Jung Kim, Kisung Kim, Hyunjung Shim, Jinhan Lee

llms agents computer-vision robotics efficiency multimodal benchmarks

arXiv Machine Learning

Jul 20

Rethinking the Global Knowledge of CLIP in Training-Free Open-Vocabulary Semantic Segmentation

arXiv:2502. 06818v4 Announce Type: replace Abstract: Recent works modify CLIP to perform open-vocabulary semantic segmentation in a training-free manner (TF-OVSS).

By Jingyun Wang, Cilin Yan, Guoliang Kang

rag computer-vision benchmarks

Related stories

QueryGaussian: Scalable and Training-Free Open-Vocabulary 3D Instance Retrieval

CORE-3D: Context-aware Open-vocabulary Retrieval by Embeddings in 3D

COVTrack++: Learning Open-Vocabulary Multi-Object Tracking from Continuous Videos via a Synergistic Paradigm

Mitigating Simplicity Bias in OOD Detection through Object Co-occurrence Analysis

Open-Vocabulary BEV Segmentation with 3D-Aware Geometric Constraints

Rethinking the Global Knowledge of CLIP in Training-Free Open-Vocabulary Semantic Segmentation