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The paper introduces OpenRef, a benchmark for Referring Expression Comprehension (REC) designed for open‑world scenarios. OpenRef expands beyond simple settings by including diverse visual domains, variable target counts (multi‑target and none‑target), and a rich vocabulary with proper nouns, polysemous words, and ordinal terms. It also proposes new evaluation metrics—F1 for grounding accuracy and N3R for negative expression rejection—and presents a training‑free Multi‑task Consistency Checker (MCC) that improves model performance with a single click.
The paper introduces Grounded Human-Attributed Description and Activity Recognition (GHADAR), a task that requires describing the characteristics and activities of every person in a video given their locations. It presents a new dataset derived from AVA-Actions with open‑set captions, a method that constrains cross‑attention masks in vision‑language models to better use grounding information, and a holistic VLM‑based evaluation schema that compares concepts directly between video and predictions. Experiments show the proposed method surpasses state‑of‑the‑art VLMs and highlight limitations of existing evaluation metrics.
arXiv:2610.10163v1 Announce Type: new Abstract: Linking people's appearance and actions to character identities is essential for understanding video narratives. We present a framework for identity-aw...
arXiv:2606. 07708v1 Announce Type: cross Abstract: We introduce a dataset and benchmark for cross-view urban traffic perception built from synchronized ego-centric bicycle videos and aerial drone videos recorded at real urban intersections.
arXiv:2606. 27876v1 Announce Type: cross Abstract: Spatial intelligence is essential for low-altitude unmanned aerial vehicle (UAV) perception, collaboration, and navigation.
arXiv:2609.09736v1 Announce Type: new Abstract: Video Temporal Grounding (VTG) localizes the video segment that matches a natural-language query. Many queries describe an action performed by a partic...