6 papers · 1 filter
Towards More Accurate Personalized Image Generation: Addressing Overfitting and Evaluation Bias
Mingxiao Li, Tingyu Qu, Tinne Tuytelaars +1
Personalized image generation via text prompts has great potential to improve daily life and professional work by facilitating the creation of customized visual content. The aim of…
TS-LLaVA: Constructing Visual Tokens through Thumbnail-and-Sampling for Training-Free Video Large Language Models
Tingyu Qu, Mingxiao Li, Tinne Tuytelaars +1
Recent advances in multimodal Large Language Models (LLMs) have shown great success in understanding multi-modal contents. For video understanding tasks, training-based video LLMs…
Animate Your Motion: Turning Still Images into Dynamic Videos
Mingxiao Li, Bo Wan, Marie-Francine Moens +1
In recent years, diffusion models have made remarkable strides in text-to-video generation, sparking a quest for enhanced control over video outputs to more accurately reflect user…
Introducing Routing Functions to Vision-Language Parameter-Efficient Fine-Tuning with Low-Rank Bottlenecks
Tingyu Qu, Tinne Tuytelaars, Marie-Francine Moens
Mainstream parameter-efficient fine-tuning (PEFT) methods, such as LoRA or Adapter, project a model's hidden states to a lower dimension, allowing pre-trained models to adapt to ne…
DM-Align: Leveraging the Power of Natural Language Instructions to Make Changes to Images
Maria Mihaela Trusca, Tinne Tuytelaars, Marie-Francine Moens
Text-based semantic image editing assumes the manipulation of an image using a natural language instruction. Although recent works are capable of generating creative and qualitativ…
Object-Attribute Binding in Text-to-Image Generation: Evaluation and Control
Maria Mihaela Trusca, Wolf Nuyts, Jonathan Thomm +4
Current diffusion models create photorealistic images given a text prompt as input but struggle to correctly bind attributes mentioned in the text to the right objects in the image…