activity
20182026
most citedIntriguing Properties of Vision Transformers

305 citations · 357 across the 27 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

LatentCRF: Continuous CRF for Efficient Latent Diffusion

Kanchana Ranasinghe, Sadeep Jayasumana, Andreas Veit +5

Latent Diffusion Models (LDMs) produce high-quality, photo-realistic images, however, the latency incurred by multiple costly inference iterations can restrict their applicability.…

cs.RO2024★ 2 cited

LLaRA: Supercharging Robot Learning Data for Vision-Language Policy

Xiang Li, Cristina Mata, Jongwoo Park +8

Vision Language Models (VLMs) have recently been leveraged to generate robotic actions, forming Vision-Language-Action (VLA) models. However, directly adapting a pretrained VLM for…

cs.CV2024

Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QA

Jongwoo Park, Kanchana Ranasinghe, Kumara Kahatapitiya +3

Long-form videos that span across wide temporal intervals are highly information redundant and contain multiple distinct events or entities that are often loosely related. Therefor…

cs.CV2024

Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMs

Kanchana Ranasinghe, Satya Narayan Shukla, Omid Poursaeed +2

Integration of Large Language Models (LLMs) into visual domain tasks, resulting in visual-LLMs (V-LLMs), has enabled exceptional performance in vision-language tasks, particularly…

cs.CV2024

Hierarchical Text-to-Vision Self Supervised Alignment for Improved Histopathology Representation Learning

Hasindri Watawana, Kanchana Ranasinghe, Tariq Mahmood +3

Self-supervised representation learning has been highly promising for histopathology image analysis with numerous approaches leveraging their patient-slide-patch hierarchy to learn…

cs.CV2024

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…

cs.CV2024

Language Repository for Long Video Understanding

Kumara Kahatapitiya, Kanchana Ranasinghe, Jongwoo Park +1

Language has become a prominent modality in computer vision with the rise of LLMs. Despite supporting long context-lengths, their effectiveness in handling long-term information gr…