16 citations · 41 across the 12 of their papers we have counts for
5 papers · 1 filter
Understanding Long Videos with Multimodal Language Models
Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya +1
Large Language Models (LLMs) have allowed recent LLM-based approaches to achieve excellent performance on long-video understanding benchmarks. We investigate how extensive world kn…
Diffusion Illusions: Hiding Images in Plain Sight
Ryan Burgert, Xiang Li, Abe Leite +2
We explore the problem of computationally generating special `prime' images that produce optical illusions when physically arranged and viewed in a certain way. First, we propose a…
Limited Data, Unlimited Potential: A Study on ViTs Augmented by Masked Autoencoders
Srijan Das, Tanmay Jain, Dominick Reilly +6
Vision Transformers (ViTs) have become ubiquitous in computer vision. Despite their success, ViTs lack inductive biases, which can make it difficult to train them with limited data…
Peekaboo: Text to Image Diffusion Models are Zero-Shot Segmentors
Ryan Burgert, Kanchana Ranasinghe, Xiang Li +1
Recently, text-to-image diffusion models have shown remarkable capabilities in creating realistic images from natural language prompts. However, few works have explored using these…
Neural Neural Textures Make Sim2Real Consistent
Ryan Burgert, Jinghuan Shang, Xiang Li +1
Unpaired image translation algorithms can be used for sim2real tasks, but many fail to generate temporally consistent results. We present a new approach that combines differentiabl…