Search Results for author: Xizhou Zhu

Found 43 papers, 36 papers with code

Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures

1 code implementation4 Mar 2024 Yuchen Duan, Weiyun Wang, Zhe Chen, Xizhou Zhu, Lewei Lu, Tong Lu, Yu Qiao, Hongsheng Li, Jifeng Dai, Wenhai Wang

Our evaluations demonstrate that VRWKV surpasses ViT's performance in image classification and has significantly faster speeds and lower memory usage processing high-resolution inputs.

Image Classification

The All-Seeing Project V2: Towards General Relation Comprehension of the Open World

1 code implementation29 Feb 2024 Weiyun Wang, Yiming Ren, Haowen Luo, Tiantong Li, Chenxiang Yan, Zhe Chen, Wenhai Wang, Qingyun Li, Lewei Lu, Xizhou Zhu, Yu Qiao, Jifeng Dai

In addition, we design a new benchmark, termed Circular-based Relation Probing Evaluation (CRPE) for comprehensively evaluating the relation comprehension capabilities of MLLMs.

Hallucination Object Localization +3

Multi-scale 2D Temporal Map Diffusion Models for Natural Language Video Localization

no code implementations16 Jan 2024 Chongzhi Zhang, Mingyuan Zhang, Zhiyang Teng, Jiayi Li, Xizhou Zhu, Lewei Lu, Ziwei Liu, Aixin Sun

Our method involves the direct generation of a global 2D temporal map via a conditional denoising diffusion process, based on the input video and language query.

Denoising Video Understanding

Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications

1 code implementation11 Jan 2024 Yuwen Xiong, Zhiqi Li, Yuntao Chen, Feng Wang, Xizhou Zhu, Jiapeng Luo, Wenhai Wang, Tong Lu, Hongsheng Li, Yu Qiao, Lewei Lu, Jie zhou, Jifeng Dai

The advancements in speed and efficiency of DCNv4, combined with its robust performance across diverse vision tasks, show its potential as a foundational building block for future vision models.

Image Classification Image Generation +1

InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

1 code implementation21 Dec 2023 Zhe Chen, Jiannan Wu, Wenhai Wang, Weijie Su, Guo Chen, Sen Xing, Muyan Zhong, Qinglong Zhang, Xizhou Zhu, Lewei Lu, Bin Li, Ping Luo, Tong Lu, Yu Qiao, Jifeng Dai

However, the progress in vision and vision-language foundation models, which are also critical elements of multi-modal AGI, has not kept pace with LLMs.

 Ranked #1 on Zero-Shot Video Retrieval on MSR-VTT-full (using extra training data)

Image Retrieval Image-to-Text Retrieval +10

Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft

no code implementations14 Dec 2023 Hao Li, Xue Yang, Zhaokai Wang, Xizhou Zhu, Jie zhou, Yu Qiao, Xiaogang Wang, Hongsheng Li, Lewei Lu, Jifeng Dai

Traditional reinforcement-learning-based agents rely on sparse rewards that often only use binary values to indicate task completion or failure.

ControlLLM: Augment Language Models with Tools by Searching on Graphs

1 code implementation26 Oct 2023 Zhaoyang Liu, Zeqiang Lai, Zhangwei Gao, Erfei Cui, Ziheng Li, Xizhou Zhu, Lewei Lu, Qifeng Chen, Yu Qiao, Jifeng Dai, Wenhai Wang

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

Scheduling

Mini-DALLE3: Interactive Text to Image by Prompting Large Language Models

1 code implementation11 Oct 2023 Zeqiang Lai, Xizhou Zhu, Jifeng Dai, Yu Qiao, Wenhai Wang

The revolution of artificial intelligence content generation has been rapidly accelerated with the booming text-to-image (T2I) diffusion models.

Code Generation Image Generation +2

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

2 code implementations9 May 2023 Zhaoyang Liu, Yinan He, Wenhai Wang, Weiyun Wang, Yi Wang, Shoufa Chen, Qinglong Zhang, Zeqiang Lai, Yang Yang, Qingyun Li, Jiashuo Yu, Kunchang Li, Zhe Chen, Xue Yang, Xizhou Zhu, Yali Wang, LiMin Wang, Ping Luo, Jifeng Dai, Yu Qiao

Different from existing interactive systems that rely on pure language, by incorporating pointing instructions, the proposed iGPT significantly improves the efficiency of communication between users and chatbots, as well as the accuracy of chatbots in vision-centric tasks, especially in complicated visual scenarios where the number of objects is greater than 2.

Language Modelling

Planning-oriented Autonomous Driving

1 code implementation CVPR 2023 Yihan Hu, Jiazhi Yang, Li Chen, Keyu Li, Chonghao Sima, Xizhou Zhu, Siqi Chai, Senyao Du, Tianwei Lin, Wenhai Wang, Lewei Lu, Xiaosong Jia, Qiang Liu, Jifeng Dai, Yu Qiao, Hongyang Li

Oriented at this, we revisit the key components within perception and prediction, and prioritize the tasks such that all these tasks contribute to planning.

Autonomous Driving Philosophy

Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks

2 code implementations CVPR 2023 Hao Li, Jinguo Zhu, Xiaohu Jiang, Xizhou Zhu, Hongsheng Li, Chun Yuan, Xiaohua Wang, Yu Qiao, Xiaogang Wang, Wenhai Wang, Jifeng Dai

In this paper, we propose Uni-Perceiver v2, which is the first generalist model capable of handling major large-scale vision and vision-language tasks with competitive performance.

Language Modelling Multi-Task Learning

Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information

1 code implementation CVPR 2023 Weijie Su, Xizhou Zhu, Chenxin Tao, Lewei Lu, Bin Li, Gao Huang, Yu Qiao, Xiaogang Wang, Jie zhou, Jifeng Dai

It has been proved that combining multiple pre-training strategies and data from various modalities/sources can greatly boost the training of large-scale models.

Ranked #2 on Semantic Segmentation on ADE20K (using extra training data)

Image Classification Long-tailed Object Detection +3

Demystify Transformers & Convolutions in Modern Image Deep Networks

1 code implementation10 Nov 2022 Xiaowei Hu, Min Shi, Weiyun Wang, Sitong Wu, Linjie Xing, Wenhai Wang, Xizhou Zhu, Lewei Lu, Jie zhou, Xiaogang Wang, Yu Qiao, Jifeng Dai

Our experiments on various tasks and an analysis of inductive bias show a significant performance boost due to advanced network-level and block-level designs, but performance differences persist among different STMs.

Image Deep Networks Spatial Token Mixer

InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

2 code implementations CVPR 2023 Wenhai Wang, Jifeng Dai, Zhe Chen, Zhenhang Huang, Zhiqi Li, Xizhou Zhu, Xiaowei Hu, Tong Lu, Lewei Lu, Hongsheng Li, Xiaogang Wang, Yu Qiao

Compared to the great progress of large-scale vision transformers (ViTs) in recent years, large-scale models based on convolutional neural networks (CNNs) are still in an early state.

 Ranked #1 on Instance Segmentation on COCO test-dev (AP50 metric, using extra training data)

Classification Image Classification +3

Siamese Image Modeling for Self-Supervised Vision Representation Learning

2 code implementations CVPR 2023 Chenxin Tao, Xizhou Zhu, Weijie Su, Gao Huang, Bin Li, Jie zhou, Yu Qiao, Xiaogang Wang, Jifeng Dai

Driven by these analysis, we propose Siamese Image Modeling (SiameseIM), which predicts the dense representations of an augmented view, based on another masked view from the same image but with different augmentations.

Representation Learning Self-Supervised Learning +1

DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation

1 code implementation16 Mar 2022 Ailing Zeng, Xuan Ju, Lei Yang, Ruiyuan Gao, Xizhou Zhu, Bo Dai, Qiang Xu

This paper proposes a simple baseline framework for video-based 2D/3D human pose estimation that can achieve 10 times efficiency improvement over existing works without any performance degradation, named DeciWatch.

2D Human Pose Estimation 3D Human Pose Estimation +2

Searching Parameterized AP Loss for Object Detection

1 code implementation NeurIPS 2021 Chenxin Tao, Zizhang Li, Xizhou Zhu, Gao Huang, Yong liu, Jifeng Dai

In this paper, we propose Parameterized AP Loss, where parameterized functions are introduced to substitute the non-differentiable components in the AP calculation.

Object object-detection +1

Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks

1 code implementation CVPR 2022 Xizhou Zhu, Jinguo Zhu, Hao Li, Xiaoshi Wu, Xiaogang Wang, Hongsheng Li, Xiaohua Wang, Jifeng Dai

The model is pre-trained on several uni-modal and multi-modal tasks, and evaluated on a variety of downstream tasks, including novel tasks that did not appear in the pre-training stage.

Collaborative Visual Navigation

1 code implementation2 Jul 2021 Haiyang Wang, Wenguan Wang, Xizhou Zhu, Jifeng Dai, LiWei Wang

As a fundamental problem for Artificial Intelligence, multi-agent system (MAS) is making rapid progress, mainly driven by multi-agent reinforcement learning (MARL) techniques.

Multi-agent Reinforcement Learning Navigate +1

AutoLoss-Zero: Searching Loss Functions from Scratch for Generic Tasks

no code implementations CVPR 2022 Hao Li, Tianwen Fu, Jifeng Dai, Hongsheng Li, Gao Huang, Xizhou Zhu

However, the automatic design of loss functions for generic tasks with various evaluation metrics remains under-investigated.

Unsupervised Object Detection with LiDAR Clues

no code implementations CVPR 2021 Hao Tian, Yuntao Chen, Jifeng Dai, Zhaoxiang Zhang, Xizhou Zhu

We further identify another major issue, seldom noticed by the community, that the long-tailed and open-ended (sub-)category distribution should be accommodated.

Object object-detection +2

Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation

1 code implementation ICLR 2021 Hao Li, Chenxin Tao, Xizhou Zhu, Xiaogang Wang, Gao Huang, Jifeng Dai

In this paper, we propose to automate the design of metric-specific loss functions by searching differentiable surrogate losses for each metric.

Semantic Segmentation

Deformable DETR: Deformable Transformers for End-to-End Object Detection

17 code implementations ICLR 2021 Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, Jifeng Dai

DETR has been recently proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance.

Real-Time Object Detection

Spatially Adaptive Inference with Stochastic Feature Sampling and Interpolation

1 code implementation ECCV 2020 Zhenda Xie, Zheng Zhang, Xizhou Zhu, Gao Huang, Stephen Lin

In the feature maps of CNNs, there commonly exists considerable spatial redundancy that leads to much repetitive processing.

Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation

2 code implementations ICLR 2020 Hang Gao, Xizhou Zhu, Steve Lin, Jifeng Dai

This is typically done by augmenting static operators with learned free-form sampling grids in the image space, dynamically tuned to the data and task for adapting the receptive field.

Image Classification Object +1

An Empirical Study of Spatial Attention Mechanisms in Deep Networks

1 code implementation ICCV 2019 Xizhou Zhu, Dazhi Cheng, Zheng Zhang, Stephen Lin, Jifeng Dai

Attention mechanisms have become a popular component in deep neural networks, yet there has been little examination of how different influencing factors and methods for computing attention from these factors affect performance.

Deformable ConvNets v2: More Deformable, Better Results

23 code implementations CVPR 2019 Xizhou Zhu, Han Hu, Stephen Lin, Jifeng Dai

The superior performance of Deformable Convolutional Networks arises from its ability to adapt to the geometric variations of objects.

Instance Segmentation Object +2

Towards High Performance Video Object Detection for Mobiles

3 code implementations16 Apr 2018 Xizhou Zhu, Jifeng Dai, Xingchi Zhu, Yichen Wei, Lu Yuan

In this paper, we present a light weight network architecture for video object detection on mobiles.

Object object-detection +2

Flow-Guided Feature Aggregation for Video Object Detection

2 code implementations ICCV 2017 Xizhou Zhu, Yujie Wang, Jifeng Dai, Lu Yuan, Yichen Wei

The accuracy of detection suffers from degenerated object appearances in videos, e. g., motion blur, video defocus, rare poses, etc.

Object object-detection +2

Deep Feature Flow for Video Recognition

3 code implementations CVPR 2017 Xizhou Zhu, Yuwen Xiong, Jifeng Dai, Lu Yuan, Yichen Wei

Yet, it is non-trivial to transfer the state-of-the-art image recognition networks to videos as per-frame evaluation is too slow and unaffordable.

Video Recognition Video Semantic Segmentation

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