22 citations · 37 across the 18 of their papers we have counts for
9 papers · 1 filter
ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance
Chunwei Wang, Guansong Lu, Junwei Yang +5
In this paper, we introduce ILLUME, a unified multimodal large language model (MLLM) that seamlessly integrates multimodal understanding and generation capabilities within a single…
JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation
Chenhan Jiang, Yihan Zeng, Tianyang Hu +4
Score Distillation Sampling (SDS) by well-trained 2D diffusion models has shown great promise in text-to-3D generation. However, this paradigm distills view-agnostic 2D image distr…
HiRes-LLaVA: Restoring Fragmentation Input in High-Resolution Large Vision-Language Models
Runhui Huang, Xinpeng Ding, Chunwei Wang +7
High-resolution inputs enable Large Vision-Language Models (LVLMs) to discern finer visual details, enhancing their comprehension capabilities. To reduce the training and computati…
DetCLIPv3: Towards Versatile Generative Open-vocabulary Object Detection
Lewei Yao, Renjie Pi, Jianhua Han +5
Existing open-vocabulary object detectors typically require a predefined set of categories from users, significantly confining their application scenarios. In this paper, we introd…
LayerDiff: Exploring Text-guided Multi-layered Composable Image Synthesis via Layer-Collaborative Diffusion Model
Runhui Huang, Kaixin Cai, Jianhua Han +6
Despite the success of generating high-quality images given any text prompts by diffusion-based generative models, prior works directly generate the entire images, but cannot provi…
OpenOcc: Open Vocabulary 3D Scene Reconstruction via Occupancy Representation
Haochen Jiang, Yueming Xu, Yihan Zeng +4
3D reconstruction has been widely used in autonomous navigation fields of mobile robotics. However, the former research can only provide the basic geometry structure without the ca…
LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement
Renyuan Peng, Xinyue Cai, Hang Xu +4
Understanding road structures is crucial for autonomous driving. Intricate road structures are often depicted using lane graphs, which include centerline curves and connections for…
Translating Images to Road Network: A Sequence-to-Sequence Perspective
Jiachen Lu, Ming Nie, Bozhou Zhang +6
The extraction of road network is essential for the generation of high-definition maps since it enables the precise localization of road landmarks and their interconnections. Howev…
Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models
Xinpeng Ding, Jinahua Han, Hang Xu +3
The rise of multimodal large language models (MLLMs) has spurred interest in language-based driving tasks. However, existing research typically focuses on limited tasks and often o…