3 papers
cs.CV2026
Consensus-Aware Multi-Source Fusion for Reference-Guided Camouflaged Object Detection
Junyang Xia, Luocheng Zhang, Wenwen Pan +4
Reference-guided camouflaged object detection aims to segment a target whose visual appearance closely resembles its surroundings by exploiting auxiliary reference samples. The tas…
cs.LG2026
FedAFD: Multimodal Federated Learning via Adversarial Fusion and Distillation
Min Tan, Junchao Ma, Yinfu Feng +6
Multimodal Federated Learning (MFL) enables clients with heterogeneous data modalities to collaboratively train models without sharing raw data, offering a privacy-preserving frame…
cs.CV2024
Imp: Highly Capable Large Multimodal Models for Mobile Devices
Zhenwei Shao, Zhou Yu, Jun Yu +5
By harnessing the capabilities of large language models (LLMs), recent large multimodal models (LMMs) have shown remarkable versatility in open-world multimodal understanding. Neve…