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20232026
most citedCo-movement Pattern Mining from Videos

2 citations · 3 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

Not Every Cue Is Evidence: Cue Supportability for Forensic Distillation in Face Forgery Detection

Binjia Zhou, Dawei Luo, Shuai Chen +7

Explainable face forgery detection requires not only correct judgments but also forensic evidence supported by the input image. However, training cues are typically derived from th…

cs.CV2026

EvolveReason: Self-Evolving Reasoning Paradigm for Explainable Deepfake Facial Image Identification

Binjia Zhou, Dawei Luo, Shuai Chen +7

With the rapid advancement of AIGC technology, developing identification methods to address the security challenges posed by deepfakes has become urgent. Face forgery identificatio…

cs.CV2025

CorrDetail: Visual Detail Enhanced Self-Correction for Face Forgery Detection

Binjia Zhou, Hengrui Lou, Lizhe Chen +6

With the swift progression of image generation technology, the widespread emergence of facial deepfakes poses significant challenges to the field of security, thus amplifying the u…

cs.CV2025

Mining Platoon Patterns from Traffic Videos

Yijun Bei, Teng Ma, Dongxiang Zhang +3

Discovering co-movement patterns from urban-scale video data sources has emerged as an attractive topic. This task aims to identify groups of objects that travel together along a c…

cs.CV2024

Fire and Smoke Detection with Burning Intensity Representation

Xiaoyi Han, Yanfei Wu, Nan Pu +4

An effective Fire and Smoke Detection (FSD) and analysis system is of paramount importance due to the destructive potential of fire disasters. However, many existing FSD methods di…

cs.CV2024

Benchmarking Multi-Scene Fire and Smoke Detection

Xiaoyi Han, Nan Pu, Zunlei Feng +4

The current irregularities in existing public Fire and Smoke Detection (FSD) datasets have become a bottleneck in the advancement of FSD technology. Upon in-depth analysis, we iden…

cs.CV2024★ 1 cited

A Large-scale Universal Evaluation Benchmark For Face Forgery Detection

Yijun Bei, Hengrui Lou, Jinsong Geng +5

With the rapid development of AI-generated content (AIGC) technology, the production of realistic fake facial images and videos that deceive human visual perception has become poss…