activity
20202026
most citedIs it enough to optimize CNN architectures on ImageNet?

29 citations · 48 across the 24 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2024

Goldfish: Vision-Language Understanding of Arbitrarily Long Videos

Kirolos Ataallah, Xiaoqian Shen, Eslam Abdelrahman +6

Most current LLM-based models for video understanding can process videos within minutes. However, they struggle with lengthy videos due to challenges such as "noise and redundancy"…

cs.CV2024

Lazy Layers to Make Fine-Tuned Diffusion Models More Traceable

Haozhe Liu, Wentian Zhang, Bing Li +2

Foundational generative models should be traceable to protect their owners and facilitate safety regulation. To achieve this, traditional approaches embed identifiers based on supe…

cs.CV2024★ 2 cited

Faster Diffusion via Temporal Attention Decomposition

Haozhe Liu, Wentian Zhang, Jinheng Xie +6

We explore the role of attention mechanism during inference in text-conditional diffusion models. Empirical observations suggest that cross-attention outputs converge to a fixed po…

cs.CV2023

Efficient Rotation Invariance in Deep Neural Networks through Artificial Mental Rotation

Lukas Tuggener, Thilo Stadelmann, Jürgen Schmidhuber

Humans and animals recognize objects irrespective of the beholder's point of view, which may drastically change their appearances. Artificial pattern recognizers also strive to ach…

cs.CV2021★ 29 cited

Is it enough to optimize CNN architectures on ImageNet?

Lukas Tuggener, Jürgen Schmidhuber, Thilo Stadelmann

Classification performance based on ImageNet is the de-facto standard metric for CNN development. In this work we challenge the notion that CNN architecture design solely based on…