4 citations · 17 across the 25 of their papers we have counts for
7 papers · 1 filter
Gaussian Harmony: Attaining Fairness in Diffusion-based Face Generation Models
Basudha Pal, Arunkumar Kannan, Ram Prabhakar Kathirvel +2
Diffusion models have achieved great progress in face generation. However, these models amplify the bias in the generation process, leading to an imbalance in distribution of sensi…
Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine Vision-Language Model
Shraman Pramanick, Guangxing Han, Rui Hou +6
The ability of large language models (LLMs) to process visual inputs has given rise to general-purpose vision systems, unifying various vision-language (VL) tasks by instruction tu…
Unsupervised Video Domain Adaptation with Masked Pre-Training and Collaborative Self-Training
Arun Reddy, William Paul, Corban Rivera +3
In this work, we tackle the problem of unsupervised domain adaptation (UDA) for video action recognition. Our approach, which we call UNITE, uses an image teacher model to adapt a…
Instruct2Attack: Language-Guided Semantic Adversarial Attacks
Jiang Liu, Chen Wei, Yuxiang Guo +5
We propose Instruct2Attack (I2A), a language-guided semantic attack that generates semantically meaningful perturbations according to free-form language instructions. We make use o…
DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics
Aniket Roy, Maiterya Suin, Anshul Shah +3
Diffusion models have advanced generative AI significantly in terms of editing and creating naturalistic images. However, efficiently improving generated image quality is still of…
VILLS -- Video-Image Learning to Learn Semantics for Person Re-Identification
Siyuan Huang, Ram Prabhakar, Yuxiang Guo +2
Person Re-identification is a research area with significant real world applications. Despite recent progress, existing methods face challenges in robust re-identification in the w…
GaitContour: Efficient Gait Recognition based on a Contour-Pose Representation
Yuxiang Guo, Anshul Shah, Jiang Liu +3
Gait recognition holds the promise to robustly identify subjects based on walking patterns instead of appearance information. In recent years, this field has been dominated by lear…