305 citations · 822 across the 79 of their papers we have counts for
19 papers · 1 filter
Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation
Sihan Liu, Yiwei Ma, Xiaoqing Zhang +4
Referring Remote Sensing Image Segmentation (RRSIS) is a new challenge that combines computer vision and natural language processing, delineating specific regions in aerial images…
X-Dreamer: Creating High-quality 3D Content by Bridging the Domain Gap Between Text-to-2D and Text-to-3D Generation
Yiwei Ma, Yijun Fan, Jiayi Ji +5
In recent times, automatic text-to-3D content creation has made significant progress, driven by the development of pretrained 2D diffusion models. Existing text-to-3D methods typic…
Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models
Qiong Wu, Wei Yu, Yiyi Zhou +3
With ever increasing parameters and computation, vision-language pre-trained (VLP) models exhibit prohibitive expenditure in downstream task adaption. Recent endeavors mainly focus…
Semi-Supervised Panoptic Narrative Grounding
Danni Yang, Jiayi Ji, Xiaoshuai Sun +4
Despite considerable progress, the advancement of Panoptic Narrative Grounding (PNG) remains hindered by costly annotations. In this paper, we introduce a novel Semi-Supervised Pan…
NICE: Improving Panoptic Narrative Detection and Segmentation with Cascading Collaborative Learning
Haowei Wang, Jiayi Ji, Tianyu Guo +4
Panoptic Narrative Detection (PND) and Segmentation (PNS) are two challenging tasks that involve identifying and locating multiple targets in an image according to a long narrative…
JM3D & JM3D-LLM: Elevating 3D Understanding with Joint Multi-modal Cues
Jiayi Ji, Haowei Wang, Changli Wu +3
The rising importance of 3D understanding, pivotal in computer vision, autonomous driving, and robotics, is evident. However, a prevailing trend, which straightforwardly resorted t…
3D-STMN: Dependency-Driven Superpoint-Text Matching Network for End-to-End 3D Referring Expression Segmentation
Changli Wu, Yiwei Ma, Qi Chen +4
In 3D Referring Expression Segmentation (3D-RES), the earlier approach adopts a two-stage paradigm, extracting segmentation proposals and then matching them with referring expressi…
Continual Face Forgery Detection via Historical Distribution Preserving
Ke Sun, Shen Chen, Taiping Yao +3
Face forgery techniques have advanced rapidly and pose serious security threats. Existing face forgery detection methods try to learn generalizable features, but they still fall sh…
Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D Representation
Haowei Wang, Jiji Tang, Jiayi Ji +8
In recent years, 3D understanding has turned to 2D vision-language pre-trained models to overcome data scarcity challenges. However, existing methods simply transfer 2D alignment s…
Towards General Visual-Linguistic Face Forgery Detection
Ke Sun, Shen Chen, Taiping Yao +4
Deepfakes are realistic face manipulations that can pose serious threats to security, privacy, and trust. Existing methods mostly treat this task as binary classification, which us…
Systematic Investigation of Sparse Perturbed Sharpness-Aware Minimization Optimizer
Peng Mi, Li Shen, Tianhe Ren +6
Deep neural networks often suffer from poor generalization due to complex and non-convex loss landscapes. Sharpness-Aware Minimization (SAM) is a popular solution that smooths the…
Adapting Pre-trained Language Models to Vision-Language Tasks via Dynamic Visual Prompting
Shubin Huang, Qiong Wu, Yiyi Zhou +4
Pre-trained language models (PLMs) have played an increasing role in multimedia research. In terms of vision-language (VL) tasks, they often serve as a language encoder and still r…
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
Gen Luo, Yiyi Zhou, Tianhe Ren +3
Recently, growing interest has been aroused in extending the multimodal capability of large language models (LLMs), e.g., vision-language (VL) learning, which is regarded as the ne…
Towards Efficient Visual Adaption via Structural Re-parameterization
Gen Luo, Minglang Huang, Yiyi Zhou +4
Parameter-efficient transfer learning (PETL) is an emerging research spot aimed at inexpensively adapting large-scale pre-trained models to downstream tasks. Recent advances have a…
Active Teacher for Semi-Supervised Object Detection
Peng Mi, Jianghang Lin, Yiyi Zhou +7
In this paper, we study teacher-student learning from the perspective of data initialization and propose a novel algorithm called Active Teacher(Source code are available at: \url{…
X-Mesh: Towards Fast and Accurate Text-driven 3D Stylization via Dynamic Textual Guidance
Yiwei Ma, Xiaioqing Zhang, Xiaoshuai Sun +5
Text-driven 3D stylization is a complex and crucial task in the fields of computer vision (CV) and computer graphics (CG), aimed at transforming a bare mesh to fit a target text. P…
Towards End-to-end Semi-supervised Learning for One-stage Object Detection
Gen Luo, Yiyi Zhou, Lei Jin +2
Semi-supervised object detection (SSOD) is a research hot spot in computer vision, which can greatly reduce the requirement for expensive bounding-box annotations. Despite great su…
Towards Local Visual Modeling for Image Captioning
Yiwei Ma, Jiayi Ji, Xiaoshuai Sun +2
In this paper, we study the local visual modeling with grid features for image captioning, which is critical for generating accurate and detailed captions. To achieve this target,…
Towards Real-Time Panoptic Narrative Grounding by an End-to-End Grounding Network
Haowei Wang, Jiayi Ji, Yiyi Zhou +2
Panoptic Narrative Grounding (PNG) is an emerging cross-modal grounding task, which locates the target regions of an image corresponding to the text description. Existing approache…