activity
20142026
most citedBlind Universal Bayesian Image Denoising with Gaussian Noise Level Learning

128 citations · 315 across the 51 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

6 papers · 2 filters

cs.CV2024

Coherent and Multi-modality Image Inpainting via Latent Space Optimization

Lingzhi Pan, Tong Zhang, Bingyuan Chen +4

With the advancements in denoising diffusion probabilistic models (DDPMs), image inpainting has significantly evolved from merely filling information based on nearby regions to gen…

cs.CV2024

AdaNCA: Neural Cellular Automata As Adaptors For More Robust Vision Transformer

Yitao Xu, Tong Zhang, Sabine Süsstrunk

Vision Transformers (ViTs) demonstrate remarkable performance in image classification through visual-token interaction learning, particularly when equipped with local information v…

cs.CV2024

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Yanhao Wu, Tong Zhang, Wei Ke +3

In the realm of point cloud scene understanding, particularly in indoor scenes, objects are arranged following human habits, resulting in objects of certain semantics being closely…

cs.CV2024

OMH: Structured Sparsity via Optimally Matched Hierarchy for Unsupervised Semantic Segmentation

Baran Ozaydin, Tong Zhang, Deblina Bhattacharjee +2

Unsupervised Semantic Segmentation (USS) involves segmenting images without relying on predefined labels, aiming to alleviate the burden of extensive human labeling. Existing metho…

cs.CV2024★ 2 cited

Emergent Dynamics in Neural Cellular Automata

Yitao Xu, Ehsan Pajouheshgar, Sabine Süsstrunk

Neural Cellular Automata (NCA) models are trainable variations of traditional Cellular Automata (CA). Emergent motion in the patterns created by NCA has been successfully applied t…

cs.CV2024★ 4 cited

NoiseNCA: Noisy Seed Improves Spatio-Temporal Continuity of Neural Cellular Automata

Ehsan Pajouheshgar, Yitao Xu, Sabine Süsstrunk

Neural Cellular Automata (NCA) is a class of Cellular Automata where the update rule is parameterized by a neural network that can be trained using gradient descent. In this paper,…