3 citations · 3 across the 7 of their papers we have counts for
7 papers
Foresee-to-Ground: From Predictive Temporal Perception to Evidence-Driven Reasoning for Video Temporal Grounding
Zelin Zheng, Xinyan Liu, Ruixin Li +4
Current Video-LLM approaches for Video Temporal Grounding (VTG) typically rely on direct timestamp generation from an unstructured visual-token stream, often leading to brittle num…
Exploring the Temporal Consistency for Point-Level Weakly-Supervised Temporal Action Localization
Yunchuan Ma, Laiyun Qing, Guorong Li +3
Point-supervised Temporal Action Localization (PTAL) adopts a lightly frame-annotated paradigm (\textit{i.e.}, labeling only a single frame per action instance) to train a model to…
Boosting Point-supervised Temporal Action Localization via Text Refinement and Alignment
Yunchuan Ma, Laiyun Qing, Guorong Li +3
Recently, point-supervised temporal action localization has gained significant attention for its effective balance between labeling costs and localization accuracy. However, curren…
SDVPT: Semantic-Driven Visual Prompt Tuning for Open-World Object Counting
Yiming Zhao, Guorong Li, Laiyun Qing +5
Open-world object counting leverages the robust text-image alignment of pre-trained vision-language models (VLMs) to enable counting of arbitrary categories in images specified by…
RETTA: Retrieval-Enhanced Test-Time Adaptation for Zero-Shot Video Captioning
Yunchuan Ma, Laiyun Qing, Guorong Li +4
Despite the significant progress of fully-supervised video captioning, zero-shot methods remain much less explored. In this paper, we propose a novel zero-shot video captioning fra…
Dynamic Erasing Network Based on Multi-Scale Temporal Features for Weakly Supervised Video Anomaly Detection
Chen Zhang, Guorong Li, Yuankai Qi +4
The goal of weakly supervised video anomaly detection is to learn a detection model using only video-level labeled data. However, prior studies typically divide videos into fixed-l…
Towards Subject-Oriented Video Captioning via User-Specified Targets
Chang Teng, Yunchuan Ma, Guorong Li +3
Describing video content according to users' needs is a long-held goal. Although existing video captioning methods have made significant progress, the generated captions may not fo…