86 citations · 116 across the 10 of their papers we have counts for
10 papers
Towards Multimodal Lifelong Understanding: A Dataset and Agentic Baseline
Guo Chen, Lidong Lu, Yicheng Liu +17
While datasets for video understanding have scaled to hour-long durations, they typically consist of densely concatenated clips that differ from natural, unscripted daily life. To…
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…
MRSN: Multi-Relation Support Network for Video Action Detection
Yin-Dong Zheng, Guo Chen, Minglei Yuan +1
Action detection is a challenging video understanding task, requiring modeling spatio-temporal and interaction relations. Current methods usually model actor-actor and actor-contex…
InternVideo-Ego4D: A Pack of Champion Solutions to Ego4D Challenges
Guo Chen, Sen Xing, Zhe Chen +18
In this report, we present our champion solutions to five tracks at Ego4D challenge. We leverage our developed InternVideo, a video foundation model, for five Ego4D tasks, includin…
Exploring State Change Capture of Heterogeneous Backbones @ Ego4D Hands and Objects Challenge 2022
Yin-Dong Zheng, Guo Chen, Jiahao Wang +2
Capturing the state changes of interacting objects is a key technology for understanding human-object interactions. This technical report describes our method using heterogeneous b…
Exploring Detection-based Method For Speaker Diarization @ Ego4D Audio-only Diarization Challenge 2022
Jiahao Wang, Guo Chen, Yin-Dong Zheng +1
We provide the technical report for Ego4D audio-only diarization challenge in ECCV 2022. Speaker diarization takes the audio streams as input and outputs the homogeneous segments a…
Uncertainty-based Network for Few-shot Image Classification
Minglei Yuan, Qian Xu, Chunhao Cai +3
The transductive inference is an effective technique in the few-shot learning task, where query sets update prototypes to improve themselves. However, these methods optimize the mo…
BasicTAD: an Astounding RGB-Only Baseline for Temporal Action Detection
Min Yang, Guo Chen, Yin-Dong Zheng +2
Temporal action detection (TAD) is extensively studied in the video understanding community by generally following the object detection pipeline in images. However, complex designs…
DCAN: Improving Temporal Action Detection via Dual Context Aggregation
Guo Chen, Yin-Dong Zheng, Limin Wang +1
Temporal action detection aims to locate the boundaries of action in the video. The current method based on boundary matching enumerates and calculates all possible boundary matchi…
Dynamic Sampling Networks for Efficient Action Recognition in Videos
Yin-Dong Zheng, Zhaoyang Liu, Tong Lu +1
The existing action recognition methods are mainly based on clip-level classifiers such as two-stream CNNs or 3D CNNs, which are trained from the randomly selected clips and applie…