Search Results for author:
Found 6 papers, 2 papers with code
Multi-Task Dense Prediction via Mixture of Low-Rank Experts
Furthermore, to control the parameters and computational cost brought by the increase in the number of experts, we take inspiration from LoRA and propose to leverage the low-rank format of a vanilla convolution in the expert network.
Empowering Segmentation Ability to Multi-modal Large Language Models
Multi-modal large language models (MLLMs) can understand image-language prompts and demonstrate impressive reasoning ability.
Improving Adversarial Energy-Based Model via Diffusion Process
Generative models have shown strong generation ability while efficient likelihood estimation is less explored.
Revisiting Single Image Reflection Removal In the Wild
This research focuses on the issue of single-image reflection removal (SIRR) in real-world conditions, examining it from two angles: the collection pipeline of real reflection pairs and the perception of real reflection locations.
Generalization and Hallucination of Large Vision-Language Models through a Camouflaged Lens
Large Vision-Language Model (LVLM) has seen burgeoning development and increasing attention recently.
WM-MoE: Weather-aware Multi-scale Mixture-of-Experts for Blind Adverse Weather Removal
To this end, we propose a method called Weather-aware Multi-scale MoE (WM-MoE) based on Transformer for blind weather removal.
