6 papers
STORM: End-to-End Referring Multi-Object Tracking in Videos
Zijia Lu, Jingru Yi, Jue Wang +4
Referring multi-object tracking (RMOT) is a task of associating all the objects in a video that semantically match with given textual queries or referring expressions. Existing RMO…
Learning Compact Video Representations for Efficient Long-form Video Understanding in Large Multimodal Models
Yuxiao Chen, Jue Wang, Zhikang Zhang +8
With recent advancements in video backbone architectures, combined with the remarkable achievements of large language models (LLMs), the analysis of long-form videos spanning tens…
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
NowYouSee Me: Context-Aware Automatic Audio Description
Seon-Ho Lee, Jue Wang, David Fan +5
Audio Description (AD) plays a pivotal role as an application system aimed at guaranteeing accessibility in multimedia content, which provides additional narrations at suitable int…
GEXIA: Granularity Expansion and Iterative Approximation for Scalable Multi-grained Video-language Learning
Yicheng Wang, Zhikang Zhang, Jue Wang +6
In various video-language learning tasks, the challenge of achieving cross-modality alignment with multi-grained data persists. We propose a method to tackle this challenge from tw…
Video Token Merging for Long-form Video Understanding
Seon-Ho Lee, Jue Wang, Zhikang Zhang +2
As the scale of data and models for video understanding rapidly expand, handling long-form video input in transformer-based models presents a practical challenge. Rather than resor…