9 citations · 46 across the 41 of their papers we have counts for
10 papers · 1 filter
Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint
Junwei Zhou, Xueting Li, Lu Qi +1
We present Layout-Your-3D, a framework that allows controllable and compositional 3D generation from text prompts. Existing text-to-3D methods often struggle to generate assets wit…
Tex4D: Zero-shot 4D Scene Texturing with Video Diffusion Models
Jingzhi Bao, Xueting Li, Ming-Hsuan Yang
3D meshes are widely used in computer vision and graphics for their efficiency in animation and minimal memory use, playing a crucial role in movies, games, AR, and VR. However, cr…
Video Prediction Transformers without Recurrence or Convolution
Yujin Tang, Lu Qi, Xiangtai Li +2
Video prediction has witnessed the emergence of RNN-based models led by ConvLSTM, and CNN-based models led by SimVP. Following the significant success of ViT, recent works have int…
LLAVADI: What Matters For Multimodal Large Language Models Distillation
Shilin Xu, Xiangtai Li, Haobo Yuan +3
The recent surge in Multimodal Large Language Models (MLLMs) has showcased their remarkable potential for achieving generalized intelligence by integrating visual understanding int…
Mamba or RWKV: Exploring High-Quality and High-Efficiency Segment Anything Model
Haobo Yuan, Xiangtai Li, Lu Qi +4
Transformer-based segmentation methods face the challenge of efficient inference when dealing with high-resolution images. Recently, several linear attention architectures, such as…
SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified Flow
Chaoyang Wang, Xiangtai Li, Lu Qi +3
Semantic segmentation and semantic image synthesis are two representative tasks in visual perception and generation. While existing methods consider them as two distinct tasks, we…
Reason3D: Searching and Reasoning 3D Segmentation via Large Language Model
Kuan-Chih Huang, Xiangtai Li, Lu Qi +2
Recent advancements in multimodal large language models (LLMs) have demonstrated significant potential across various domains, particularly in concept reasoning. However, their app…
Training Class-Imbalanced Diffusion Model Via Overlap Optimization
Divin Yan, Lu Qi, Vincent Tao Hu +2
Diffusion models have made significant advances recently in high-quality image synthesis and related tasks. However, diffusion models trained on real-world datasets, which often fo…
High-Quality Entity Segmentation and Grounding
Lu Qi, Yi-Wen Chen, Tao Zhang +4
In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, the proposed dataset naming EntitySeg co…
RMP-SAM: Towards Real-Time Multi-Purpose Segment Anything
Shilin Xu, Haobo Yuan, Qingyu Shi +9
Recent segmentation methods, which adopt large-scale data training and transformer architecture, aim to create one foundation model that can perform multiple tasks. However, most o…