1 citations · 4 across the 10 of their papers we have counts for
10 papers
Taming Real-World Space-Time Video Super-Resolution with One-Step Diffusion
Shuoyan Wei, Feng Li, Chen Zhou +3
Diffusion models have demonstrated exceptional success in video super-resolution (VSR), exhibiting powerful capabilities for generating fine-grained details. However, their potenti…
Towards Robust and Generalizable Continuous Space-Time Video Super-Resolution with Events
Shuoyan Wei, Feng Li, Shengeng Tang +4
Continuous space-time video super-resolution (C-STVSR) has garnered increasing interest for its capability to reconstruct high-resolution and high-frame-rate videos at arbitrary sp…
Harnessing Group-Oriented Consistency Constraints for Semi-Supervised Semantic Segmentation in CdZnTe Semiconductors
Peihao Li, Yan Fang, Man Liu +4
Labeling Cadmium Zinc Telluride (CdZnTe) semiconductor images is challenging due to the low-contrast defect boundaries, necessitating annotators to cross-reference multiple views.…
EvEnhancer: Empowering Effectiveness, Efficiency and Generalizability for Continuous Space-Time Video Super-Resolution with Events
Shuoyan Wei, Feng Li, Shengeng Tang +2
Continuous space-time video super-resolution (C-STVSR) endeavors to upscale videos simultaneously at arbitrary spatial and temporal scales, which has recently garnered increasing i…
PSVMA+: Exploring Multi-granularity Semantic-visual Adaption for Generalized Zero-shot Learning
Man Liu, Huihui Bai, Feng Li +5
Generalized zero-shot learning (GZSL) endeavors to identify the unseen categories using knowledge from the seen domain, necessitating the intrinsic interactions between the visual…
Attend and Enrich: Enhanced Visual Prompt for Zero-Shot Learning
Man Liu, Huihui Bai, Feng Li +4
Zero-shot learning (ZSL) endeavors to transfer knowledge from seen categories to recognize unseen categories, which mostly relies on the semantic-visual interactions between image…
Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptation
Anqi Li, Feng Li, Yuxi Liu +3
Although recent generative image compression methods have demonstrated impressive potential in optimizing the rate-distortion-perception trade-off, they still face the critical cha…
BlindDiff: Empowering Degradation Modelling in Diffusion Models for Blind Image Super-Resolution
Feng Li, Yixuan Wu, Zichao Liang +4
Diffusion models (DM) have achieved remarkable promise in image super-resolution (SR). However, most of them are tailored to solving non-blind inverse problems with fixed known deg…
Towards the Uncharted: Density-Descending Feature Perturbation for Semi-supervised Semantic Segmentation
Xiaoyang Wang, Huihui Bai, Limin Yu +2
Semi-supervised semantic segmentation allows model to mine effective supervision from unlabeled data to complement label-guided training. Recent research has primarily focused on c…
Region-Adaptive Transform with Segmentation Prior for Image Compression
Yuxi Liu, Wenhan Yang, Huihui Bai +2
Learned Image Compression (LIC) has shown remarkable progress in recent years. Existing works commonly employ CNN-based or self-attention-based modules as transform methods for com…