2 citations · 3 across the 11 of their papers we have counts for
11 papers
Subtractive Modulative Network with Learnable Periodic Activations
Tiou Wang, Zhuoqian Yang, Markus Flierl +2
We propose the Subtractive Modulative Network (SMN), a novel, parameter-efficient Implicit Neural Representation (INR) architecture inspired by classical subtractive synthesis. The…
2-Shots in the Dark: Low-Light Denoising with Minimal Data Acquisition
Liying Lu, Raphaël Achddou, Sabine Süsstrunk
Raw images taken in low-light conditions are very noisy due to low photon count and sensor noise. Learning-based denoisers have the potential to reconstruct high-quality images. Fo…
Enhancing Frequency Forgery Clues for Diffusion-Generated Image Detection
Daichi Zhang, Tong Zhang, Shiming Ge +1
Diffusion models have achieved remarkable success in image synthesis, but the generated high-quality images raise concerns about potential malicious use. Existing detectors often s…
Leveraging Hierarchical Image-Text Misalignment for Universal Fake Image Detection
Daichi Zhang, Tong Zhang, Jianmin Bao +2
With the rapid development of generative models, detecting generated fake images to prevent their malicious use has become a critical issue recently. Existing methods frame this ch…
Canonical Latent Representations in Conditional Diffusion Models
Yitao Xu, Tong Zhang, Ehsan Pajouheshgar +1
Conditional diffusion models (CDMs) have shown impressive performance across a range of generative tasks. Their ability to model the full data distribution has opened new avenues f…
Neural Cellular Automata: From Cells to Pixels
Ehsan Pajouheshgar, Yitao Xu, Ali Abbasi +3
Neural Cellular Automata (NCAs) are bio-inspired dynamical systems in which identical cells iteratively apply a learned local update rule to self-organize into complex patterns, ex…
VGRP-Bench: Visual Grid Reasoning Puzzle Benchmark for Large Vision-Language Models
Yufan Ren, Konstantinos Tertikas, Shalini Maiti +4
Large Vision-Language Models (LVLMs) struggle with puzzles, which require precise perception, rule comprehension, and logical reasoning. Assessing and enhancing their performance i…
FDS: Frequency-Aware Denoising Score for Text-Guided Latent Diffusion Image Editing
Yufan Ren, Zicong Jiang, Tong Zhang +2
Text-guided image editing using Text-to-Image (T2I) models often fails to yield satisfactory results, frequently introducing unintended modifications, such as the loss of local det…
Volumetric Temporal Texture Synthesis for Smoke Stylization using Neural Cellular Automata
Dongqing Wang, Ehsan Pajouheshgar, Yitao Xu +2
Artistic stylization of 3D volumetric smoke data is still a challenge in computer graphics due to the difficulty of ensuring spatiotemporal consistency given a reference style imag…
Unlocking Comics: The AI4VA Dataset for Visual Understanding
Peter Grönquist, Deblina Bhattacharjee, Bahar Aydemir +4
In the evolving landscape of deep learning, there is a pressing need for more comprehensive datasets capable of training models across multiple modalities. Concurrently, in digital…
Data Augmentation via Latent Diffusion for Saliency Prediction
Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang +2
Saliency prediction models are constrained by the limited diversity and quantity of labeled data. Standard data augmentation techniques such as rotating and cropping alter scene co…