Search Results for author: Dongze Lian

Found 22 papers, 17 papers with code

DreamDrone

no code implementations14 Dec 2023 Hanyang Kong, Dongze Lian, Michael Bi Mi, Xinchao Wang

We introduce DreamDrone, an innovative method for generating unbounded flythrough scenes from textual prompts.

Perpetual View Generation Scene Generation

TSP-Transformer: Task-Specific Prompts Boosted Transformer for Holistic Scene Understanding

1 code implementation6 Nov 2023 Shuo Wang, Jing Li, Zibo Zhao, Dongze Lian, Binbin Huang, Xiaomei Wang, Zhengxin Li, Shenghua Gao

Holistic scene understanding includes semantic segmentation, surface normal estimation, object boundary detection, depth estimation, etc.

Boundary Detection Depth Estimation +5

GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph

1 code implementation NeurIPS 2023 Xin Li, Dongze Lian, Zhihe Lu, Jiawang Bai, Zhibo Chen, Xinchao Wang

To mitigate that, we propose an effective adapter-style tuning strategy, dubbed GraphAdapter, which performs the textual adapter by explicitly modeling the dual-modality structure knowledge (i. e., the correlation of different semantics/classes in textual and visual modalities) with a dual knowledge graph.

Transfer Learning

Priority-Centric Human Motion Generation in Discrete Latent Space

no code implementations ICCV 2023 Hanyang Kong, Kehong Gong, Dongze Lian, Michael Bi Mi, Xinchao Wang

We also present a motion discrete diffusion model that employs an innovative noise schedule, determined by the significance of each motion token within the entire motion sequence.

Dataset Quantization

1 code implementation ICCV 2023 Daquan Zhou, Kai Wang, Jianyang Gu, Xiangyu Peng, Dongze Lian, Yifan Zhang, Yang You, Jiashi Feng

Extensive experiments demonstrate that DQ is able to generate condensed small datasets for training unseen network architectures with state-of-the-art compression ratios for lossless model training.

object-detection Object Detection +2

Weakly Supervised Video Representation Learning with Unaligned Text for Sequential Videos

1 code implementation CVPR 2023 Sixun Dong, Huazhang Hu, Dongze Lian, Weixin Luo, Yicheng Qian, Shenghua Gao

Sequential video understanding, as an emerging video understanding task, has driven lots of researchers' attention because of its goal-oriented nature.

Representation Learning Sentence +1

iQuery: Instruments as Queries for Audio-Visual Sound Separation

1 code implementation CVPR 2023 Jiaben Chen, Renrui Zhang, Dongze Lian, Jiaqi Yang, Ziyao Zeng, Jianbo Shi

To generalize to a new instrument or event class, drawing inspiration from the text-prompt design, we insert an additional query as an audio prompt while freezing the attention mechanism.

Disentanglement

Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning

1 code implementation17 Oct 2022 Dongze Lian, Daquan Zhou, Jiashi Feng, Xinchao Wang

With the proposed SSF, our model obtains 2. 46% (90. 72% vs. 88. 54%) and 11. 48% (73. 10% vs. 65. 57%) performance improvement on FGVC and VTAB-1k in terms of Top-1 accuracy compared to the full fine-tuning but only fine-tuning about 0. 3M parameters.

Image Classification

TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting

1 code implementation CVPR 2022 Huazhang Hu, Sixun Dong, Yiqun Zhao, Dongze Lian, Zhengxin Li, Shenghua Gao

Existing methods focus on performing repetitive action counting in short videos, which is tough for dealing with longer videos in more realistic scenarios.

Repetitive Action Counting

SVIP: Sequence VerIfication for Procedures in Videos

1 code implementation CVPR 2022 Yicheng Qian, Weixin Luo, Dongze Lian, Xu Tang, Peilin Zhao, Shenghua Gao

In this paper, we propose a novel sequence verification task that aims to distinguish positive video pairs performing the same action sequence from negative ones with step-level transformations but still conducting the same task.

Action Detection Action Recognition

AS-MLP: An Axial Shifted MLP Architecture for Vision

2 code implementations ICLR 2022 Dongze Lian, Zehao Yu, Xing Sun, Shenghua Gao

Our proposed AS-MLP obtains 51. 5 mAP on the COCO validation set and 49. 5 MS mIoU on the ADE20K dataset, which is competitive compared to the transformer-based architectures.

object-detection Object Detection +1

Look Before You Leap: Learning Landmark Features for One-Stage Visual Grounding

1 code implementation CVPR 2021 Binbin Huang, Dongze Lian, Weixin Luo, Shenghua Gao

Then we combine the contextual information from the landmark feature convolution module with the target's visual features for grounding.

Descriptive Object +1

Crowd Counting With Partial Annotations in an Image

1 code implementation ICCV 2021 Yanyu Xu, Ziming Zhong, Dongze Lian, Jing Li, Zhengxin Li, Xinxing Xu, Shenghua Gao

To fully leverage the data captured from different scenes with different view angles while reducing the annotation cost, this paper studies a novel crowd counting setting, i. e. only using partial annotations in each image as training data.

Active Learning Crowd Counting

Towards Fast Adaptation of Neural Architectures with Meta Learning

1 code implementation ICLR 2020 Dongze Lian, Yin Zheng, Yintao Xu, Yanxiong Lu, Leyu Lin, Peilin Zhao, Junzhou Huang, Shenghua Gao

Recently, Neural Architecture Search (NAS) has been successfully applied to multiple artificial intelligence areas and shows better performance compared with hand-designed networks.

Few-Shot Learning Neural Architecture Search

Believe It or Not, We Know What You Are Looking at!

1 code implementation4 Jul 2019 Dongze Lian, Zehao Yu, Shenghua Gao

There are two merits for our two-stage solution based gaze following: i) our solution mimics the behavior of human in gaze following, therefore it is more psychological plausible; ii) besides using heatmap to supervise the output of our network, we can also leverage gaze direction to facilitate the training of gaze direction pathway, therefore our network can be more robustly trained.

Density Map Regression Guided Detection Network for RGB-D Crowd Counting and Localization

no code implementations CVPR 2019 Dongze Lian, Jing Li, Jia Zheng, Weixin Luo, Shenghua Gao

Specifically, to improve the robustness of detection-based approaches for small/tiny heads, we leverage density map to improve the head/non-head classification in detection network where density map serves as the probability of a pixel being a head.

Crowd Counting regression

Evaluating Capability of Deep Neural Networks for Image Classification via Information Plane

no code implementations ECCV 2018 Hao Cheng, Dongze Lian, Shenghua Gao, Yanlin Geng

Inspired by the pioneering work of information bottleneck principle for Deep Neural Networks (DNNs) analysis, we design an information plane based framework to evaluate the capability of DNNs for image classification tasks, which not only helps understand the capability of DNNs, but also helps us choose a neural network which leads to higher classification accuracy more efficiently.

General Classification Image Classification +1

Future Frame Prediction for Anomaly Detection – A New Baseline

1 code implementation CVPR 2018 Wen Liu, Weixin Luo, Dongze Lian, Shenghua Gao

To predict a future frame with higher quality for normal events, other than the commonly used appearance (spatial) constraints on intensity and gradient, we also introduce a motion (temporal) constraint in video prediction by enforcing the optical flow between predicted frames and ground truth frames to be consistent, and this is the first work that introduces a temporal constraint into the video prediction task.

Anomaly Detection Optical Flow Estimation +1

Future Frame Prediction for Anomaly Detection -- A New Baseline

1 code implementation28 Dec 2017 Wen Liu, Weixin Luo, Dongze Lian, Shenghua Gao

To predict a future frame with higher quality for normal events, other than the commonly used appearance (spatial) constraints on intensity and gradient, we also introduce a motion (temporal) constraint in video prediction by enforcing the optical flow between predicted frames and ground truth frames to be consistent, and this is the first work that introduces a temporal constraint into the video prediction task.

Anomaly Detection Optical Flow Estimation +2

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