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cs.CV2026

InsHuman: Towards Natural and Identity-Preserving Human Insertion

Jie Li, Shulian Zhang, Yangyang Gao +4

Human insertion aims to naturally place specific individuals into a target background. Although existing image editing models may have such ability, they often produce failure case…

cs.CV2026

ZOTTA: Test-Time Adaptation with Gradient-Free Zeroth-Order Optimization

Ronghao Zhang, Shuaicheng Niu, Qi Deng +3

Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods rely on backpropagation (BP), wh…

cs.CV2025

VividFace: High-Quality and Efficient One-Step Diffusion For Video Face Enhancement

Shulian Zhang, Yong Guo, Long Peng +6

Video Face Enhancement (VFE) aims to restore high-quality facial regions from degraded video sequences, enabling a wide range of practical applications. Despite substantial progres…

cs.CV2024

Gap Preserving Distillation by Building Bidirectional Mappings with A Dynamic Teacher

Yong Guo, Shulian Zhang, Haolin Pan +3

Knowledge distillation aims to transfer knowledge from a large teacher model to a compact student counterpart, often coming with a significant performance gap between them. We find…

cs.CV20241 cited

Enhanced Long-Tailed Recognition with Contrastive CutMix Augmentation

Haolin Pan, Yong Guo, Mianjie Yu +1

Real-world data often follows a long-tailed distribution, where a few head classes occupy most of the data and a large number of tail classes only contain very limited samples. In…