10 papers
Motion-Aware Transformer for Multi-Object Tracking
Xu Yang, Gady Agam
Multi-object tracking (MOT) in videos remains challenging due to complex object motions and crowded scenes. Recent DETR-based frameworks offer end-to-end solutions but typically pr…
MaskMed: Decoupled Mask and Class Prediction for Medical Image Segmentation
Bin Xie, Gady Agam
Medical image segmentation typically adopts a point-wise convolutional segmentation head to predict dense labels, where each output channel is heuristically tied to a specific clas…
MSLoRA: Multi-Scale Low-Rank Adaptation via Attention Reweighting
Xu Yang, Gady Agam
We introduce MSLoRA, a backbone-agnostic, parameter-efficient adapter that reweights feature responses rather than re-tuning the underlying backbone. Existing low-rank adaptation m…
MaskSAM: Towards Auto-prompt SAM with Mask Classification for Volumetric Medical Image Segmentation
Bin Xie, Hao Tang, Bin Duan +3
Segment Anything Model (SAM), a prompt-driven foundation model for natural image segmentation, has demonstrated impressive zero-shot performance. However, SAM does not work when di…
MM-UNet: Meta Mamba UNet for Medical Image Segmentation
Bin Xie, Yan Yan, Gady Agam
State Space Models (SSMs) have recently demonstrated outstanding performance in long-sequence modeling, particularly in natural language processing. However, their direct applicati…
RFMedSAM 2: Automatic Prompt Refinement for Enhanced Volumetric Medical Image Segmentation with SAM 2
Bin Xie, Hao Tang, Yan Yan +1
Segment Anything Model 2 (SAM 2), a prompt-driven foundation model extending SAM to both image and video domains, has shown superior zero-shot performance compared to its predecess…