2 citations · 5 across the 12 of their papers we have counts for
6 papers · 1 filter
Region-R1: Reinforcing Query-Side Region Cropping for Multi-Modal Re-Ranking
Chan-Wei Hu, Zhengzhong Tu
Multi-modal retrieval-augmented generation (MM-RAG) relies heavily on re-rankers to surface the most relevant evidence for image-question queries. However, standard re-rankers typi…
AdaRing: Towards Ultra-Light Vision-Language Adaptation via Cross-Layer Tensor Ring Decomposition
Ying Huang, Yuanbin Man, Wenqi Jia +3
Adapter-based fine-tuning has gained remarkable attention in adapting large pre-trained vision language models (VLMs) for a wide range of downstream tasks efficiently. In this para…
HFMF: Hierarchical Fusion Meets Multi-Stream Models for Deepfake Detection
Anant Mehta, Bryant McArthur, Nagarjuna Kolloju +1
The rapid progress in deep generative models has led to the creation of incredibly realistic synthetic images that are becoming increasingly difficult to distinguish from real-worl…
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Kangfu Mei, Zhengzhong Tu, Mauricio Delbracio +3
We study the scaling properties of latent diffusion models (LDMs) with an emphasis on their sampling efficiency. While improved network architecture and inference algorithms have s…
SPIRE: Semantic Prompt-Driven Image Restoration
Chenyang Qi, Zhengzhong Tu, Keren Ye +4
Text-driven diffusion models have become increasingly popular for various image editing tasks, including inpainting, stylization, and object replacement. However, it still remains…
CoDi: Conditional Diffusion Distillation for Higher-Fidelity and Faster Image Generation
Kangfu Mei, Mauricio Delbracio, Hossein Talebi +3
Large generative diffusion models have revolutionized text-to-image generation and offer immense potential for conditional generation tasks such as image enhancement, restoration,…