93 citations · 148 across the 19 of their papers we have counts for
22 papers
OmniStream: Mastering Perception, Reconstruction and Action in Continuous Streams
Yibin Yan, Jilan Xu, Shangzhe Di +2
Modern visual agents require representations that are general, causal, and physically structured to operate in real-time streaming environments. However, current vision foundation…
Re-purposing Multimodal Large Language Models for Audio-Text Retrieval
Jilan Xu, Carl Thomé, Danijela Horak +2
Audio-text retrieval is crucial for bridging acoustic signals and natural language. While contrastive dual-encoder architectures like CLAP have shown promise, they are fundamentall…
EgoThinker: Unveiling Egocentric Reasoning with Spatio-Temporal CoT
Baoqi Pei, Yifei Huang, Jilan Xu +5
Egocentric video reasoning centers on an unobservable agent behind the camera who dynamically shapes the environment, requiring inference of hidden intentions and recognition of fi…
EgoExoBench: A Benchmark for First- and Third-person View Video Understanding in MLLMs
Yuping He, Yifei Huang, Guo Chen +4
Transferring and integrating knowledge across first-person (egocentric) and third-person (exocentric) viewpoints is intrinsic to human intelligence, enabling humans to learn from o…
Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision
Yuping He, Yifei Huang, Guo Chen +5
Perceiving the world from both egocentric (first-person) and exocentric (third-person) perspectives is fundamental to human cognition, enabling rich and complementary understanding…
TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
Fanheng Kong, Jingyuan Zhang, Hongzhi Zhang +7
Videos are unique in their integration of temporal elements, including camera, scene, action, and attribute, along with their dynamic relationships over time. However, existing ben…
EgoExo-Gen: Ego-centric Video Prediction by Watching Exo-centric Videos
Jilan Xu, Yifei Huang, Baoqi Pei +6
Generating videos in the first-person perspective has broad application prospects in the field of augmented reality and embodied intelligence. In this work, we explore the cross-vi…
Learning Streaming Video Representation via Multitask Training
Yibin Yan, Jilan Xu, Shangzhe Di +6
Understanding continuous video streams plays a fundamental role in real-time applications including embodied AI and autonomous driving. Unlike offline video understanding, streamin…
An Egocentric Vision-Language Model based Portable Real-time Smart Assistant
Yifei Huang, Jilan Xu, Baoqi Pei +16
We present Vinci, a vision-language system designed to provide real-time, comprehensive AI assistance on portable devices. At its core, Vinci leverages EgoVideo-VL, a novel model t…
Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation Learning
Baoqi Pei, Yifei Huang, Jilan Xu +8
In egocentric video understanding, the motion of hands and objects as well as their interactions play a significant role by nature. However, existing egocentric video representatio…
Vinci: A Real-time Embodied Smart Assistant based on Egocentric Vision-Language Model
Yifei Huang, Jilan Xu, Baoqi Pei +15
We introduce Vinci, a real-time embodied smart assistant built upon an egocentric vision-language model. Designed for deployment on portable devices such as smartphones and wearabl…
CG-Bench: Clue-grounded Question Answering Benchmark for Long Video Understanding
Guo Chen, Yicheng Liu, Yifei Huang +6
Most existing video understanding benchmarks for multimodal large language models (MLLMs) focus only on short videos. The limited number of benchmarks for long video understanding…
EgoVideo: Exploring Egocentric Foundation Model and Downstream Adaptation
Baoqi Pei, Guo Chen, Jilan Xu +8
In this report, we present our solutions to the EgoVis Challenges in CVPR 2024, including five tracks in the Ego4D challenge and three tracks in the EPIC-Kitchens challenge. Buildi…
Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding
Guo Chen, Yifei Huang, Jilan Xu +7
Understanding videos is one of the fundamental directions in computer vision research, with extensive efforts dedicated to exploring various architectures such as RNN, 3D CNN, and…
EgoExoLearn: A Dataset for Bridging Asynchronous Ego- and Exo-centric View of Procedural Activities in Real World
Yifei Huang, Guo Chen, Jilan Xu +8
Being able to map the activities of others into one's own point of view is one fundamental human skill even from a very early age. Taking a step toward understanding this human abi…
InternVideo2: Scaling Foundation Models for Multimodal Video Understanding
Yi Wang, Kunchang Li, Xinhao Li +17
We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the state-of-the-art results in video recognition, video-text tasks, and video-centric dialog…
Retrieval-Augmented Egocentric Video Captioning
Jilan Xu, Yifei Huang, Junlin Hou +4
Understanding human actions from videos of first-person view poses significant challenges. Most prior approaches explore representation learning on egocentric videos only, while ov…
MVBench: A Comprehensive Multi-modal Video Understanding Benchmark
Kunchang Li, Yali Wang, Yinan He +9
With the rapid development of Multi-modal Large Language Models (MLLMs), a number of diagnostic benchmarks have recently emerged to evaluate the comprehension capabilities of these…
VideoLLM: Modeling Video Sequence with Large Language Models
Guo Chen, Yin-Dong Zheng, Jiahao Wang +8
With the exponential growth of video data, there is an urgent need for automated technology to analyze and comprehend video content. However, existing video understanding models ar…
Mask Hierarchical Features For Self-Supervised Learning
Fenggang Liu, Yangguang Li, Feng Liang +3
This paper shows that Masking the Deep hierarchical features is an efficient self-supervised method, denoted as MaskDeep. MaskDeep treats each patch in the representation space as…
Learning Open-vocabulary Semantic Segmentation Models From Natural Language Supervision
Jilan Xu, Junlin Hou, Yuejie Zhang +4
In this paper, we consider the problem of open-vocabulary semantic segmentation (OVS), which aims to segment objects of arbitrary classes instead of pre-defined, closed-set categor…
InternVideo: General Video Foundation Models via Generative and Discriminative Learning
Yi Wang, Kunchang Li, Yizhuo Li +14
The foundation models have recently shown excellent performance on a variety of downstream tasks in computer vision. However, most existing vision foundation models simply focus on…