2 citations · 5 across the 27 of their papers we have counts for
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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…
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…
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…
Beyond Document Page Classification: Design, Datasets, and Challenges
Jordy Van Landeghem, Sanket Biswas, Matthew B. Blaschko +1
This paper highlights the need to bring document classification benchmarking closer to real-world applications, both in the nature of data tested (: multi-channel, multi-paged,…
Visually-Aware Context Modeling for News Image Captioning
Tingyu Qu, Tinne Tuytelaars, Marie-Francine Moens
News Image Captioning aims to create captions from news articles and images, emphasizing the connection between textual context and visual elements. Recognizing the significance of…
Multimodal Distillation for Egocentric Action Recognition
Gorjan Radevski, Dusan Grujicic, Marie-Francine Moens +2
The focal point of egocentric video understanding is modelling hand-object interactions. Standard models, e.g. CNNs or Vision Transformers, which receive RGB frames as input perfor…
Weakly Supervised Face Naming with Symmetry-Enhanced Contrastive Loss
Tingyu Qu, Tinne Tuytelaars, Marie-Francine Moens
We revisit the weakly supervised cross-modal face-name alignment task; that is, given an image and a caption, we label the faces in the image with the names occurring in the captio…