2 citations · 5 across the 5 of their papers we have counts for
5 papers
Are Large Kernels Better Teachers than Transformers for ConvNets?
Tianjin Huang, Lu Yin, Zhenyu Zhang +5
This paper reveals a new appeal of the recently emerged large-kernel Convolutional Neural Networks (ConvNets): as the teacher in Knowledge Distillation (KD) for small-kernel ConvNe…
Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution
Ming Cheng, Haoyu Ma, Qiufang Ma +7
Multi-stage strategies are frequently employed in image restoration tasks. While transformer-based methods have exhibited high efficiency in single-image super-resolution tasks, th…
OPDN: Omnidirectional Position-aware Deformable Network for Omnidirectional Image Super-Resolution
Xiaopeng Sun, Weiqi Li, Zhenyu Zhang +8
360° omnidirectional images have gained research attention due to their immersive and interactive experience, particularly in AR/VR applications. However, they suffer from lower an…
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
Shiwei Liu, Tianlong Chen, Zhenyu Zhang +4
Sparse Neural Networks (SNNs) have received voluminous attention predominantly due to growing computational and memory footprints of consistently exploding parameter count in large…
Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?
Ruisi Cai, Zhenyu Zhang, Zhangyang Wang
Given a robust model trained to be resilient to one or multiple types of distribution shifts (e.g., natural image corruptions), how is that "robustness" encoded in the model weight…