6 papers
Context Forcing: Consistent Autoregressive Video Generation with Long Context
Shuo Chen, Cong Wei, Sun Sun +5
Recent approaches to real-time long video generation typically employ streaming tuning strategies, attempting to train a long-context student using a short-context (memoryless) tea…
DreamComposer++: Empowering Diffusion Models with Multi-View Conditions for 3D Content Generation
Yunhan Yang, Shuo Chen, Yukun Huang +6
Recent advancements in leveraging pre-trained 2D diffusion models achieve the generation of high-quality novel views from a single in-the-wild image. However, existing works face c…
Selftok: Discrete Visual Tokens of Autoregression, by Diffusion, and for Reasoning
Bohan Wang, Zhongqi Yue, Fengda Zhang +15
We completely discard the conventional spatial prior in image representation and introduce a novel discrete visual tokenizer: Self-consistency Tokenizer (Selftok). At its design co…
OpenSeg-R: Improving Open-Vocabulary Segmentation via Step-by-Step Visual Reasoning
Zongyan Han, Jiale Cao, Shuo Chen +3
Open-Vocabulary Segmentation (OVS) has drawn increasing attention for its capacity to generalize segmentation beyond predefined categories. However, existing methods typically pred…
DiST-4D: Disentangled Spatiotemporal Diffusion with Metric Depth for 4D Driving Scene Generation
Jiazhe Guo, Yikang Ding, Xiwu Chen +8
Current generative models struggle to synthesize dynamic 4D driving scenes that simultaneously support temporal extrapolation and spatial novel view synthesis (NVS) without per-sce…
Revisiting Prompt Pretraining of Vision-Language Models
Zhenyuan Chen, Lingfeng Yang, Shuo Chen +3
Prompt learning is an effective method to customize Vision-Language Models (VLMs) for various downstream tasks, involving tuning very few parameters of input prompt tokens. Recentl…