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cs.CV2026

HFP-SAM: Hierarchical Frequency Prompted SAM for Efficient Marine Animal Segmentation

Pingping Zhang, Tianyu Yan, Yuhao Wang +7

Marine Animal Segmentation (MAS) aims at identifying and segmenting marine animals from complex marine environments. Most of previous deep learning-based MAS methods struggle with…

cs.CV2024

MambaPro: Multi-Modal Object Re-Identification with Mamba Aggregation and Synergistic Prompt

Yuhao Wang, Xuehu Liu, Tianyu Yan +4

Multi-modal object Re-IDentification (ReID) aims to retrieve specific objects by utilizing complementary image information from different modalities. Recently, large-scale pre-trai…

cs.CV2024

DeMo: Decoupled Feature-Based Mixture of Experts for Multi-Modal Object Re-Identification

Yuhao Wang, Yang Liu, Aihua Zheng +1

Multi-modal object Re-IDentification (ReID) aims to retrieve specific objects by combining complementary information from multiple modalities. Existing multi-modal object ReID meth…

cs.CV2024

MAS-SAM: Segment Any Marine Animal with Aggregated Features

Tianyu Yan, Zifu Wan, Xinhao Deng +3

Recently, Segment Anything Model (SAM) shows exceptional performance in generating high-quality object masks and achieving zero-shot image segmentation. However, as a versatile vis…

cs.CV2024

Fantastic Animals and Where to Find Them: Segment Any Marine Animal with Dual SAM

Pingping Zhang, Tianyu Yan, Yang Liu +1

As an important pillar of underwater intelligence, Marine Animal Segmentation (MAS) involves segmenting animals within marine environments. Previous methods don't excel in extracti…

cs.CV2024

Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

Pingping Zhang, Yuhao Wang, Yang Liu +2

Single-modal object re-identification (ReID) faces great challenges in maintaining robustness within complex visual scenarios. In contrast, multi-modal object ReID utilizes complem…