3 citations · 5 across the 5 of their papers we have counts for
6 papers · 1 filter
SynVAR: Synergizing Spatial and Semantic Alignment in Visual Autoregressive Model
Zhennan Chen, Tianxing Shi, Pengcheng Xu +5
VAR has gained widespread popularity due to its next-scale prediction paradigm. However, it faces substantial performance bottlenecks when handling complex scenes with multiple obj…
MotionSight: Boosting Fine-Grained Motion Understanding in Multimodal LLMs
Yipeng Du, Tiehan Fan, Kepan Nan +6
Despite advancements in Multimodal Large Language Models (MLLMs), their proficiency in fine-grained video motion understanding remains critically limited. They often lack inter-fra…
InstanceCap: Improving Text-to-Video Generation via Instance-aware Structured Caption
Tiehan Fan, Kepan Nan, Rui Xie +6
Text-to-video generation has evolved rapidly in recent years, delivering remarkable results. Training typically relies on video-caption paired data, which plays a crucial role in e…
OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation
Kepan Nan, Rui Xie, Penghao Zhou +6
Text-to-video (T2V) generation has recently garnered significant attention thanks to the large multi-modality model Sora. However, T2V generation still faces two important challeng…
Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation
Nian Liu, Kepan Nan, Wangbo Zhao +7
Few-Shot Video Object Segmentation (FSVOS) aims to segment objects in a query video with the same category defined by a few annotated support images. However, this task was seldom…
Learning Referring Video Object Segmentation from Weak Annotation
Wangbo Zhao, Kepan Nan, Songyang Zhang +3
Referring video object segmentation (RVOS) is a task that aims to segment the target object in all video frames based on a sentence describing the object. Although existing RVOS me…