10 citations · 22 across the 11 of their papers we have counts for
11 papers
Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification
Wujian Peng, Lingchen Meng, Yuxuan Cai +7
Unified Multimodal Modeling aims to integrate visual understanding and generation within a single system. However, existing approaches typically rely on two disparate visual tokeni…
Reason, Then Re-reason: Cross-view Revisiting Improves Spatial Reasoning
Chaofan Ma, Zhenjie Mao, Yuhuan Yang +5
Spatial reasoning from egocentric videos is inherently challenging because the observable evidence is constrained by the camera trajectory. Existing methods rely on single-turn inf…
GenMask: Adapting DiT for Segmentation via Direct Mask Generation
Yuhuan Yang, Xianwei Zhuang, Yuxuan Cai +6
Recent approaches for segmentation have leveraged pretrained generative models as feature extractors, treating segmentation as a downstream adaptation task via indirect feature ret…
SaFiRe: Saccade-Fixation Reiteration with Mamba for Referring Image Segmentation
Zhenjie Mao, Yuhuan Yang, Chaofan Ma +4
Referring Image Segmentation (RIS) aims to segment the target object in an image given a natural language expression. While recent methods leverage pre-trained vision backbones and…
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
Yuhuan Yang, Chaofan Ma, Zhenjie Mao +3
Video understanding is a complex challenge that requires effective modeling of spatial-temporal dynamics. With the success of image foundation models (IFMs) in image understanding,…
ReMamber: Referring Image Segmentation with Mamba Twister
Yuhuan Yang, Chaofan Ma, Jiangchao Yao +3
Referring Image Segmentation~(RIS) leveraging transformers has achieved great success on the interpretation of complex visual-language tasks. However, the quadratic computation cos…
AttrSeg: Open-Vocabulary Semantic Segmentation via Attribute Decomposition-Aggregation
Chaofan Ma, Yuhuan Yang, Chen Ju +3
Open-vocabulary semantic segmentation is a challenging task that requires segmenting novel object categories at inference time. Recent studies have explored vision-language pre-tra…
Multi-Modal Prototypes for Open-World Semantic Segmentation
Yuhuan Yang, Chaofan Ma, Chen Ju +4
In semantic segmentation, generalizing a visual system to both seen categories and novel categories at inference time has always been practically valuable yet challenging. To enabl…
DiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery
Chaofan Ma, Yuhuan Yang, Chen Ju +5
Learning from a large corpus of data, pre-trained models have achieved impressive progress nowadays. As popular generative pre-training, diffusion models capture both low-level vis…
Open-vocabulary Semantic Segmentation with Frozen Vision-Language Models
Chaofan Ma, Yuhuan Yang, Yanfeng Wang +2
When trained at a sufficient scale, self-supervised learning has exhibited a notable ability to solve a wide range of visual or language understanding tasks. In this paper, we inve…
Transforming the Interactive Segmentation for Medical Imaging
Wentao Liu, Chaofan Ma, Yuhuan Yang +2
The goal of this paper is to interactively refine the automatic segmentation on challenging structures that fall behind human performance, either due to the scarcity of available a…