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most citedEfficient Diffusion-Based 3D Human Pose Estimation with Hierarchical Temporal Pruning

4 citations · 5 across the 10 of their papers we have counts for

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cs.CV2026

Toward Fine-Grained Facial Control in 3D Talking Head Generation

Shaoyang Xie, Xiaofeng Cong, Baosheng Yu +4

Audio-driven talking head generation is a core component of digital avatars, and 3D Gaussian Splatting has shown strong performance in real-time rendering of high-fidelity talking…

cs.CV2025

Revisiting Adversarial Training under Hyperspectral Image

Weihua Zhang, Chengze Jiang, Minjing Dong +5

Recent studies have shown that deep learning-based hyperspectral image (HSI) classification models are highly vulnerable to adversarial attacks, posing significant security risks.…

cs.CV2025

Efficient Diffusion-Based 3D Human Pose Estimation with Hierarchical Temporal Pruning

Yuquan Bi, Hongsong Wang, Xinli Shi +3

Diffusion models have demonstrated strong capabilities in generating high-fidelity 3D human poses, yet their iterative nature and multi-hypothesis requirements incur substantial co…

cs.CV2024

Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation

Xiaofeng Cong, Jing Zhang, Yeying Jin +5

Underwater images often suffer from quality degradation due to absorption and scattering effects. Most existing underwater image enhancement algorithms produce a single, fixed-colo…

cs.CV2024

Improving Fast Adversarial Training via Self-Knowledge Guidance

Chengze Jiang, Junkai Wang, Minjing Dong +5

Adversarial training has achieved remarkable advancements in defending against adversarial attacks. Among them, fast adversarial training (FAT) is gaining attention for its ability…

cs.CV2024

Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspective

Jie Gui, Chengze Jiang, Minjing Dong +4

While adversarial training is an effective defense method against adversarial attacks, it notably increases the training cost. To this end, fast adversarial training (FAT) is prese…