activity
20192026
most citedDynamic Sampling Networks for Efficient Action Recognition in Videos

86 citations · 212 across the 24 of their papers we have counts for

collaborators
Showing cs.CVShow all

18 papers · 1 filter

cs.CV2025

ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data

Zhaoyang Liu, Jingjing Xie, Zichen Ding +27

Vision-Language Models (VLMs) have enabled computer use agents (CUAs) that operate GUIs autonomously, showing great potential, yet progress is limited by the lack of large-scale, o…

cs.CV2025★ 4 cited

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Weiyun Wang, Zhangwei Gao, Lixin Gu +72

We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…

cs.CV2025★ 1 cited

MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents

Xuehui Wang, Zhenyu Wu, JingJing Xie +25

We introduce MMBench-GUI, a hierarchical benchmark for evaluating GUI automation agents across Windows, macOS, Linux, iOS, Android, and Web platforms. It comprises four levels: GUI…

cs.CV2025★ 8 cited

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Jinguo Zhu, Weiyun Wang, Zhe Chen +48

We introduce InternVL3, a significant advancement in the InternVL series featuring a native multimodal pre-training paradigm. Rather than adapting a text-only large language model…

cs.CV2024★ 16 cited

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Zhe Chen, Weiyun Wang, Yue Cao +39

We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…

cs.CV2024★ 5 cited

VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks

Jiannan Wu, Muyan Zhong, Sen Xing +10

We present VisionLLM v2, an end-to-end generalist multimodal large model (MLLM) that unifies visual perception, understanding, and generation within a single framework. Unlike trad…

cs.CV2024

VidMuse: A Simple Video-to-Music Generation Framework with Long-Short-Term Modeling

Zeyue Tian, Zhaoyang Liu, Ruibin Yuan +6

In this work, we systematically study music generation conditioned solely on the video. First, we present a large-scale dataset comprising 360K video-music pairs, including various…

cs.CV2023★ 5 cited

ControlLLM: Augment Language Models with Tools by Searching on Graphs

Zhaoyang Liu, Zeqiang Lai, Zhangwei Gao +8

We present ControlLLM, a novel framework that enables large language models (LLMs) to utilize multi-modal tools for solving complex real-world tasks. Despite the remarkable perform…

cs.CV2023★ 14 cited

InternGPT: Solving Vision-Centric Tasks by Interacting with ChatGPT Beyond Language

Zhaoyang Liu, Yinan He, Wenhai Wang +17

We present an interactive visual framework named InternGPT, or iGPT for short. The framework integrates chatbots that have planning and reasoning capabilities, such as ChatGPT, wit…

cs.CV2022

VLG: General Video Recognition with Web Textual Knowledge

Jintao Lin, Zhaoyang Liu, Wenhai Wang +2

Video recognition in an open and dynamic world is quite challenging, as we need to handle different settings such as close-set, long-tail, few-shot and open-set. By leveraging sema…

cs.CV2022★ 10 cited

MotionBERT: A Unified Perspective on Learning Human Motion Representations

Wentao Zhu, Xiaoxuan Ma, Zhaoyang Liu +3

We present a unified perspective on tackling various human-centric video tasks by learning human motion representations from large-scale and heterogeneous data resources. Specifica…

cs.CV2022★ 1 cited

Submission to Generic Event Boundary Detection Challenge@CVPR 2022: Local Context Modeling and Global Boundary Decoding Approach

Jiaqi Tang, Zhaoyang Liu, Jing Tan +3

Generic event boundary detection (GEBD) is an important yet challenging task in video understanding, which aims at detecting the moments where humans naturally perceive event bound…

cs.CV2022

Joint-Modal Label Denoising for Weakly-Supervised Audio-Visual Video Parsing

Haoyue Cheng, Zhaoyang Liu, Hang Zhou +3

This paper focuses on the weakly-supervised audio-visual video parsing task, which aims to recognize all events belonging to each modality and localize their temporal boundaries. T…

cs.CV2021★ 1 cited

Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection

Jiaqi Tang, Zhaoyang Liu, Chen Qian +2

Generic event boundary detection is an important yet challenging task in video understanding, which aims at detecting the moments where humans naturally perceive event boundaries.…

cs.CV2021★ 8 cited

DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results

Liming Jiang, Zhengkui Guo, Wayne Wu +18

This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection. The challenge employs the DeeperForensics-1.0 dataset, one of the…

cs.CV2020★ 86 cited

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…

cs.CV2020★ 23 cited

TAM: Temporal Adaptive Module for Video Recognition

Zhaoyang Liu, Limin Wang, Wayne Wu +2

Video data is with complex temporal dynamics due to various factors such as camera motion, speed variation, and different activities. To effectively capture this diverse motion pat…

cs.CV2019★ 28 cited

TEINet: Towards an Efficient Architecture for Video Recognition

Zhaoyang Liu, Donghao Luo, Yabiao Wang +6

Efficiency is an important issue in designing video architectures for action recognition. 3D CNNs have witnessed remarkable progress in action recognition from videos. However, com…