6 papers
Unifying Heterogeneous Multi-Modal Remote Sensing Detection Via Language-Pivoted Pretraining
Yuxuan Li, Yuming Chen, Yunheng Li +3
Heterogeneous multi-modal remote sensing object detection aims to accurately detect objects from diverse sensors (e.g., RGB, SAR, Infrared). Existing approaches largely adopt a lat…
OmniSegmentor: A Flexible Multi-Modal Learning Framework for Semantic Segmentation
Bo-Wen Yin, Jiao-Long Cao, Xuying Zhang +3
Recent research on representation learning has proved the merits of multi-modal clues for robust semantic segmentation. Nevertheless, a flexible pretrain-and-finetune pipeline for…
OneVAE: Joint Discrete and Continuous Optimization Helps Discrete Video VAE Train Better
Yupeng Zhou, Zhen Li, Ziheng Ouyang +8
Encoding videos into discrete tokens could align with text tokens to facilitate concise and unified multi-modal LLMs, yet introducing significant spatiotemporal compression compare…
Re-Aligning Language to Visual Objects with an Agentic Workflow
Yuming Chen, Jiangyan Feng, Haodong Zhang +6
Language-based object detection (LOD) aims to align visual objects with language expressions. A large amount of paired data is utilized to improve LOD model generalizations. During…
TeMO: Towards Text-Driven 3D Stylization for Multi-Object Meshes
Xuying Zhang, Bo-Wen Yin, Yuming Chen +4
Recent progress in the text-driven 3D stylization of a single object has been considerably promoted by CLIP-based methods. However, the stylization of multi-object 3D scenes is sti…
Zone Evaluation: Revealing Spatial Bias in Object Detection
Zhaohui Zheng, Yuming Chen, Qibin Hou +3
A fundamental limitation of object detectors is that they suffer from "spatial bias", and in particular perform less satisfactorily when detecting objects near image borders. For a…