2 citations · 2 across the 6 of their papers we have counts for
6 papers
Rethinking MLLM Itself as a Segmenter with a Single Segmentation Token
Anqi Zhang, Xiaokang Ji, Guangyu Gao +3
Recent segmentation methods leveraging Multi-modal Large Language Models (MLLMs) have shown reliable object-level segmentation and enhanced spatial perception. However, almost all…
Few Exemplar-Based General Medical Image Segmentation via Domain-Aware Selective Adaptation
Chen Xu, Qiming Huang, Yuqi Hou +4
Medical image segmentation poses challenges due to domain gaps, data modality variations, and dependency on domain knowledge or experts, especially for low- and middle-income count…
Frame Interpolation with Consecutive Brownian Bridge Diffusion
Zonglin Lyu, Ming Li, Jianbo Jiao +1
Recent work in Video Frame Interpolation (VFI) tries to formulate VFI as a diffusion-based conditional image generation problem, synthesizing the intermediate frame given a random…
360+x: A Panoptic Multi-modal Scene Understanding Dataset
Hao Chen, Yuqi Hou, Chenyuan Qu +3
Human perception of the world is shaped by a multitude of viewpoints and modalities. While many existing datasets focus on scene understanding from a certain perspective (e.g. egoc…
Multi-view Self-supervised Disentanglement for General Image Denoising
Hao Chen, Chenyuan Qu, Yu Zhang +2
With its significant performance improvements, the deep learning paradigm has become a standard tool for modern image denoisers. While promising performance has been shown on seen…
Med-Tuning: A New Parameter-Efficient Tuning Framework for Medical Volumetric Segmentation
Jiachen Shen, Wenxuan Wang, Chen Chen +5
The "pre-training then fine-tuning (FT)" paradigm is widely adopted to boost the model performance of deep learning-based methods for medical volumetric segmentation. However, conv…