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20232026
most citedDynamic Erasing Network Based on Multi-Scale Temporal Features for Weakly Supervised Video Anomaly Detection

3 citations · 5 across the 11 of their papers we have counts for

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10 papers · 1 filter

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

The Devil is in the Distributions: Explicit Modeling of Scene Content is Key in Zero-Shot Video Captioning

Mingkai Tian, Guorong Li, Yuankai Qi +4

Zero-shot video captioning requires that a model generate high-quality captions without human-annotated video-text pairs for training. State-of-the-art approaches to the problem le…

cs.CV2024

Adapter-Enhanced Semantic Prompting for Continual Learning

Baocai Yin, Ji Zhao, Huajie Jiang +5

Continual learning (CL) enables models to adapt to evolving data streams. A major challenge of CL is catastrophic forgetting, where new knowledge will overwrite previously acquired…

cs.CV2024

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…

cs.CV2024★ 1 cited

Generating Content for HDR Deghosting from Frequency View

Tao Hu, Qingsen Yan, Yuankai Qi +1

Recovering ghost-free High Dynamic Range (HDR) images from multiple Low Dynamic Range (LDR) images becomes challenging when the LDR images exhibit saturation and significant motion…

cs.CV2023

Weakly Supervised Video Individual CountingWeakly Supervised Video Individual Counting

Xinyan Liu, Guorong Li, Yuankai Qi +5

Video Individual Counting (VIC) aims to predict the number of unique individuals in a single video. % Existing methods learn representations based on trajectory labels for individu…

cs.CV2023★ 3 cited

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…

cs.CV2023

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…