activity
20232025
most citedSignVTCL: Multi-Modal Continuous Sign Language Recognition Enhanced by Visual-Textual Contrastive Learning

5 citations · 11 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2025

SceneDecorator: Towards Scene-Oriented Story Generation with Scene Planning and Scene Consistency

Quanjian Song, Donghao Zhou, Jingyu Lin +5

Recent text-to-image models have revolutionized image generation, but they still struggle with maintaining concept consistency across generated images. While existing works focus o…

cs.CV2025

Medical Large Vision Language Models with Multi-Image Visual Ability

Xikai Yang, Juzheng Miao, Yuchen Yuan +4

Medical large vision-language models (LVLMs) have demonstrated promising performance across various single-image question answering (QA) benchmarks, yet their capability in process…

cs.CV2025

SciVerse: Unveiling the Knowledge Comprehension and Visual Reasoning of LMMs on Multi-modal Scientific Problems

Ziyu Guo, Ray Zhang, Hao Chen +4

The rapid advancement of Large Multi-modal Models (LMMs) has enabled their application in scientific problem-solving, yet their fine-grained capabilities remain under-explored. In…

cs.CV2024★ 1 cited

Point Cloud Understanding via Attention-Driven Contrastive Learning

Yi Wang, Jiaze Wang, Ziyu Guo +5

Recently Transformer-based models have advanced point cloud understanding by leveraging self-attention mechanisms, however, these methods often overlook latent information in less…

cs.CV2024

MagicTailor: Component-Controllable Personalization in Text-to-Image Diffusion Models

Donghao Zhou, Jiancheng Huang, Jinbin Bai +5

Text-to-image diffusion models can generate high-quality images but lack fine-grained control of visual concepts, limiting their creativity. Thus, we introduce component-controllab…

cs.CV2024★ 1 cited

SFANet: Spatial-Frequency Attention Network for Weather Forecasting

Jiaze Wang, Hao Chen, Hongcan Xu +7

Weather forecasting plays a critical role in various sectors, driving decision-making and risk management. However, traditional methods often struggle to capture the complex dynami…

cs.CV2024

MM-Mixing: Multi-Modal Mixing Alignment for 3D Understanding

Jiaze Wang, Yi Wang, Ziyu Guo +5

We introduce MM-Mixing, a multi-modal mixing alignment framework for 3D understanding. MM-Mixing applies mixing-based methods to multi-modal data, preserving and optimizing cross-m…

cs.CV2024★ 5 cited

SignVTCL: Multi-Modal Continuous Sign Language Recognition Enhanced by Visual-Textual Contrastive Learning

Hao Chen, Jiaze Wang, Ziyu Guo +6

Sign language recognition (SLR) plays a vital role in facilitating communication for the hearing-impaired community. SLR is a weakly supervised task where entire videos are annotat…

cs.CV2023★ 3 cited

Traj-MAE: Masked Autoencoders for Trajectory Prediction

Hao Chen, Jiaze Wang, Kun Shao +5

Trajectory prediction has been a crucial task in building a reliable autonomous driving system by anticipating possible dangers. One key issue is to generate consistent trajectory…

cs.CV2023

PointPatchMix: Point Cloud Mixing with Patch Scoring

Yi Wang, Jiaze Wang, Jinpeng Li +4

Data augmentation is an effective regularization strategy for mitigating overfitting in deep neural networks, and it plays a crucial role in 3D vision tasks, where the point cloud…

cs.LG2023★ 1 cited

DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction

Bowen Wang, Chen Liang, Jiaze Wang +7

Attaining the equilibrium state of a catalyst-adsorbate system is key to fundamentally assessing its effective properties, such as adsorption energy. Machine learning methods with…