Search Results for author: Gang Yu

Found 75 papers, 43 papers with code

LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning

1 code implementation30 Nov 2023 Sijin Chen, Xin Chen, Chi Zhang, Mingsheng Li, Gang Yu, Hao Fei, Hongyuan Zhu, Jiayuan Fan, Tao Chen

However, developing LMMs that can comprehend, reason, and plan in complex and diverse 3D environments remains a challenging topic, especially considering the demand for understanding permutation-invariant point cloud 3D representations of the 3D scene.

3D dense captioning Dense Captioning +1

ShapeGPT: 3D Shape Generation with A Unified Multi-modal Language Model

1 code implementation29 Nov 2023 Fukun Yin, Xin Chen, Chi Zhang, Biao Jiang, Zibo Zhao, Jiayuan Fan, Gang Yu, Taihao Li, Tao Chen

The advent of large language models, enabling flexibility through instruction-driven approaches, has revolutionized many traditional generative tasks, but large models for 3D data, particularly in comprehensively handling 3D shapes with other modalities, are still under-explored.

3D Shape Generation Language Modelling

ChartLlama: A Multimodal LLM for Chart Understanding and Generation

no code implementations27 Nov 2023 Yucheng Han, Chi Zhang, Xin Chen, Xu Yang, Zhibin Wang, Gang Yu, Bin Fu, Hanwang Zhang

Next, we introduce ChartLlama, a multi-modal large language model that we've trained using our created dataset.

Language Modelling Large Language Model

VQ-NeRF: Vector Quantization Enhances Implicit Neural Representations

no code implementations23 Oct 2023 Yiying Yang, Wen Liu, Fukun Yin, Xin Chen, Gang Yu, Jiayuan Fan, Tao Chen

Recent advancements in implicit neural representations have contributed to high-fidelity surface reconstruction and photorealistic novel view synthesis.

Novel View Synthesis Quantization +1

TapMo: Shape-aware Motion Generation of Skeleton-free Characters

no code implementations19 Oct 2023 Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen, Xiaohang Zhan, Gang Yu, Ying Shan

In this work, we present TapMo, a Text-driven Animation Pipeline for synthesizing Motion in a broad spectrum of skeleton-free 3D characters.

Robust Geometry-Preserving Depth Estimation Using Differentiable Rendering

no code implementations ICCV 2023 Chi Zhang, Wei Yin, Gang Yu, Zhibin Wang, Tao Chen, Bin Fu, Joey Tianyi Zhou, Chunhua Shen

In this paper, we propose a learning framework that trains models to predict geometry-preserving depth without requiring extra data or annotations.

Monocular Depth Estimation

Vote2Cap-DETR++: Decoupling Localization and Describing for End-to-End 3D Dense Captioning

1 code implementation6 Sep 2023 Sijin Chen, Hongyuan Zhu, Mingsheng Li, Xin Chen, Peng Guo, Yinjie Lei, Gang Yu, Taihao Li, Tao Chen

Moreover, we argue that object localization and description generation require different levels of scene understanding, which could be challenging for a shared set of queries to capture.

3D dense captioning Dense Captioning +2

IT3D: Improved Text-to-3D Generation with Explicit View Synthesis

1 code implementation22 Aug 2023 YiWen Chen, Chi Zhang, Xiaofeng Yang, Zhongang Cai, Gang Yu, Lei Yang, Guosheng Lin

Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs).

Text to 3D

StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data

1 code implementation20 Aug 2023 Yanda Li, Chi Zhang, Gang Yu, Zhibin Wang, Bin Fu, Guosheng Lin, Chunhua Shen, Ling Chen, Yunchao Wei

The remarkable multimodal capabilities demonstrated by OpenAI's GPT-4 have sparked significant interest in the development of multimodal Large Language Models (LLMs).

Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Image

1 code implementation ICCV 2023 Wei Yin, Chi Zhang, Hao Chen, Zhipeng Cai, Gang Yu, Kaixuan Wang, Xiaozhi Chen, Chunhua Shen

State-of-the-art (SOTA) monocular metric depth estimation methods can only handle a single camera model and are unable to perform mixed-data training due to the metric ambiguity.

Ranked #11 on Monocular Depth Estimation on NYU-Depth V2 (using extra training data)

Image Reconstruction Monocular Depth Estimation

Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation

1 code implementation NeurIPS 2023 Zibo Zhao, Wen Liu, Xin Chen, Xianfang Zeng, Rui Wang, Pei Cheng, Bin Fu, Tao Chen, Gang Yu, Shenghua Gao

We present a novel alignment-before-generation approach to tackle the challenging task of generating general 3D shapes based on 2D images or texts.

3D Shape Generation

MotionGPT: Human Motion as a Foreign Language

1 code implementation NeurIPS 2023 Biao Jiang, Xin Chen, Wen Liu, Jingyi Yu, Gang Yu, Tao Chen

Building upon this "motion vocabulary", we perform language modeling on both motion and text in a unified manner, treating human motion as a specific language.

Language Modelling motion prediction +1

STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection

1 code implementation CVPR 2023 Zhenglin Zhou, Huaxia Li, Hong Liu, Nanyang Wang, Gang Yu, Rongrong Ji

To solve this problem, we propose a Self-adapTive Ambiguity Reduction (STAR) loss by exploiting the properties of semantic ambiguity.

Face Alignment Facial Landmark Detection

Synchro-Transient-Extracting Transform for the Analysis of Signals with Both Harmonic and Impulsive Components

no code implementations2 Jun 2023 Yunlong Ma, Gang Yu, Tianran Lin, Qingtang Jiang

The technique aims to combine the advantages of SET and TET to generate energy concentrated representations for both harmonic and impulsive components of the signal.

StyleAvatar3D: Leveraging Image-Text Diffusion Models for High-Fidelity 3D Avatar Generation

2 code implementations30 May 2023 Chi Zhang, YiWen Chen, Yijun Fu, Zhenglin Zhou, Gang Yu, Billzb Wang, Bin Fu, Tao Chen, Guosheng Lin, Chunhua Shen

The recent advancements in image-text diffusion models have stimulated research interest in large-scale 3D generative models.

Disentangled Pre-training for Image Matting

no code implementations3 Apr 2023 Yanda Li, Zilong Huang, Gang Yu, Ling Chen, Yunchao Wei, Jianbo Jiao

The pre-training task is designed in a similar manner as image matting, where random trimap and alpha matte are generated to achieve an image disentanglement objective.

Disentanglement Image Matting

SeaFormer: Squeeze-enhanced Axial Transformer for Mobile Semantic Segmentation

1 code implementation30 Jan 2023 Qiang Wan, Zilong Huang, Jiachen Lu, Gang Yu, Li Zhang

Coupled with a light segmentation head, we achieve the best trade-off between segmentation accuracy and latency on the ARM-based mobile devices on the ADE20K and Cityscapes datasets.

Image Classification Segmentation +1

End-to-End 3D Dense Captioning with Vote2Cap-DETR

1 code implementation CVPR 2023 Sijin Chen, Hongyuan Zhu, Xin Chen, Yinjie Lei, Tao Chen, Gang Yu

Compared with prior arts, our framework has several appealing advantages: 1) Without resorting to numerous hand-crafted components, our method is based on a full transformer encoder-decoder architecture with a learnable vote query driven object decoder, and a caption decoder that produces the dense captions in a set-prediction manner.

3D dense captioning Dense Captioning

Executing your Commands via Motion Diffusion in Latent Space

1 code implementation CVPR 2023 Xin Chen, Biao Jiang, Wen Liu, Zilong Huang, Bin Fu, Tao Chen, Jingyi Yu, Gang Yu

We study a challenging task, conditional human motion generation, which produces plausible human motion sequences according to various conditional inputs, such as action classes or textual descriptors.

Motion Synthesis

Learning Variational Motion Prior for Video-based Motion Capture

no code implementations27 Oct 2022 Xin Chen, Zhuo Su, Lingbo Yang, Pei Cheng, Lan Xu, Bin Fu, Gang Yu

To improve the generalization capacity of prior space, we propose a transformer-based variational autoencoder pretrained over marker-based 3D mocap data, with a novel style-mapping block to boost the generation quality.

Pose Estimation

Coordinates Are NOT Lonely -- Codebook Prior Helps Implicit Neural 3D Representations

1 code implementation20 Oct 2022 Fukun Yin, Wen Liu, Zilong Huang, Pei Cheng, Tao Chen, Gang Yu

Implicit neural 3D representation has achieved impressive results in surface or scene reconstruction and novel view synthesis, which typically uses the coordinate-based multi-layer perceptrons (MLPs) to learn a continuous scene representation.

Novel View Synthesis

D&D: Learning Human Dynamics from Dynamic Camera

1 code implementation19 Sep 2022 Jiefeng Li, Siyuan Bian, Chao Xu, Gang Liu, Gang Yu, Cewu Lu

In this work, we present D&D (Learning Human Dynamics from Dynamic Camera), which leverages the laws of physics to reconstruct 3D human motion from the in-the-wild videos with a moving camera.

3D Human Pose Estimation Human Dynamics

Enhancing Quality of Pose-varied Face Restoration with Local Weak Feature Sensing and GAN Prior

no code implementations28 May 2022 Kai Hu, Yu Liu, Renhe Liu, Wei Lu, Gang Yu, Bin Fu

In the asymmetric codec, we adopt a mixed multi-path residual block (MMRB) to gradually extract weak texture features of input images, which can better preserve the original facial features and avoid excessive fantasy.

Blind Face Restoration Super-Resolution

Preparing data for pathological artificial intelligence with clinical-grade performance

no code implementations22 May 2022 Yuanqing Yang, Kai Sun, Yanhua Gao, Kuangsong Wang, Gang Yu

The digital pathology is fundamental of clinical-grade PAI, and the techniques of data standardization and weakly supervised learning methods based on whole slide image (WSI) are effective ways to overcome obstacles of performance reproduction.

Weakly-supervised Learning

Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization

no code implementations26 Apr 2022 Dezhao Zhu, Jiang Guo, Gang Yu, C. Y. Zhao, Hong Wang, Shenghong Ju

Designing thermal radiation metamaterials is challenging especially for problems with high degrees of freedom and complex objective.

Bayesian Optimization

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation

3 code implementations CVPR 2022 Wenqiang Zhang, Zilong Huang, Guozhong Luo, Tao Chen, Xinggang Wang, Wenyu Liu, Gang Yu, Chunhua Shen

Although vision transformers (ViTs) have achieved great success in computer vision, the heavy computational cost hampers their applications to dense prediction tasks such as semantic segmentation on mobile devices.

Segmentation Semantic Segmentation

An Energy-concentrated Wavelet Transform for Time Frequency Analysis of Transient Signals

no code implementations22 Feb 2022 Haoran Dong, Gang Yu

Transient signals are often composed of a series of modes that have multivalued time-dependent instantaneous frequency (IF), which brings challenges to the development of signal processing technology.

Attribute-specific Control Units in StyleGAN for Fine-grained Image Manipulation

1 code implementation25 Nov 2021 Rui Wang, Jian Chen, Gang Yu, Li Sun, Changqian Yu, Changxin Gao, Nong Sang

Image manipulation with StyleGAN has been an increasing concern in recent years. Recent works have achieved tremendous success in analyzing several semantic latent spaces to edit the attributes of the generated images. However, due to the limited semantic and spatial manipulation precision in these latent spaces, the existing endeavors are defeated in fine-grained StyleGAN image manipulation, i. e., local attribute translation. To address this issue, we discover attribute-specific control units, which consist of multiple channels of feature maps and modulation styles.

Image Manipulation

Fine-grained Identity Preserving Landmark Synthesis for Face Reenactment

no code implementations10 Oct 2021 Haichao Zhang, Youcheng Ben, Weixi Zhang, Tao Chen, Gang Yu, Bin Fu

Recent face reenactment works are limited by the coarse reference landmarks, leading to unsatisfactory identity preserving performance due to the distribution gap between the manipulated landmarks and those sampled from a real person.

Face Reenactment

Sketch Me A Video

no code implementations10 Oct 2021 Haichao Zhang, Gang Yu, Tao Chen, Guozhong Luo

Video creation has been an attractive yet challenging task for artists to explore.

Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification

no code implementations30 Aug 2021 Yike Wu, Bo Zhang, Gang Yu, Weixi Zhang, Bin Wang, Tao Chen, Jiayuan Fan

The goal of few-shot fine-grained image classification is to recognize rarely seen fine-grained objects in the query set, given only a few samples of this class in the support set.

Fine-Grained Image Classification Semantic correspondence +2

Identification of Pediatric Respiratory Diseases Using Fine-grained Diagnosis System

no code implementations24 Aug 2021 Gang Yu, Zhongzhi Yu, Yemin Shi, Yingshuo Wang, Xiaoqing Liu, Zheming Li, Yonggen Zhao, Fenglei Sun, Yizhou Yu, Qiang Shu

The first stage structuralizes test results by extracting relevant numerical values from clinical notes, and the disease identification stage provides a diagnosis based on text-form clinical notes and the structured data obtained from the first stage.

Shuffle Transformer with Feature Alignment for Video Face Parsing

no code implementations16 Jun 2021 Rui Zhang, Yang Han, Zilong Huang, Pei Cheng, Guozhong Luo, Gang Yu, Bin Fu

This is a short technical report introducing the solution of the Team TCParser for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021.

Face Parsing

Multi-scale super-resolution generation of low-resolution scanned pathological images

1 code implementation15 May 2021 Kai Sun, Yanhua Gao, Ting Xie, Xun Wang, Qingqing Yang, Le Chen, Kuansong Wang, Gang Yu

We design a strategy to scan slides with low resolution (5X) and a super-resolution method is proposed to restore the image details when in diagnosis.

SSIM Super-Resolution

BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation

7 code implementations5 Apr 2020 Changqian Yu, Changxin Gao, Jingbo Wang, Gang Yu, Chunhua Shen, Nong Sang

We propose to treat these spatial details and categorical semantics separately to achieve high accuracy and high efficiency for realtime semantic segmentation.

Real-Time Semantic Segmentation Segmentation

Context Prior for Scene Segmentation

2 code implementations CVPR 2020 Changqian Yu, Jingbo Wang, Changxin Gao, Gang Yu, Chunhua Shen, Nong Sang

Given an input image and corresponding ground truth, Affinity Loss constructs an ideal affinity map to supervise the learning of Context Prior.

Scene Segmentation Scene Understanding +1

High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification

2 code implementations CVPR 2020 Guan'an Wang, Shuo Yang, Huanyu Liu, Zhicheng Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, Jian Sun

When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.

Graph Matching Person Re-Identification

State-Aware Tracker for Real-Time Video Object Segmentation

1 code implementation CVPR 2020 Xi Chen, Zuoxin Li, Ye Yuan, Gang Yu, Jianxin Shen, Donglian Qi

For higher efficiency, SAT takes advantage of the inter-frame consistency and deals with each target object as a tracklet.

Segmentation Semantic Segmentation +2

Real-Time Semantic Segmentation via Multiply Spatial Fusion Network

no code implementations17 Nov 2019 Haiyang Si, Zhiqiang Zhang, Feifan Lv, Gang Yu, Feng Lu

Specifically, it achieves 77. 1% Mean IOU on the Cityscapes test dataset with the speed of 41 FPS for a 1024*2048 input, and 75. 4% Mean IOU with the speed of 91 FPS on the Camvid test dataset.

Autonomous Driving Playing the Game of 2048 +2

SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines

4 code implementations14 Nov 2019 Yinda Xu, Zeyu Wang, Zuoxin Li, Ye Yuan, Gang Yu

Following these guidelines, we design our Fully Convolutional Siamese tracker++ (SiamFC++) by introducing both classification and target state estimation branch(G1), classification score without ambiguity(G2), tracking without prior knowledge(G3), and estimation quality score(G4).

Ranked #2 on Visual Object Tracking on VOT2017/18 (using extra training data)

Classification General Classification +3

Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection

3 code implementations26 Aug 2019 Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, Gang Yu

This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019).

3D Object Detection Autonomous Driving +1

Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

6 code implementations ICCV 2019 Wenhai Wang, Enze Xie, Xiaoge Song, Yuhang Zang, Wenjia Wang, Tong Lu, Gang Yu, Chunhua Shen

Recently, some methods have been proposed to tackle arbitrary-shaped text detection, but they rarely take the speed of the entire pipeline into consideration, which may fall short in practical applications. In this paper, we propose an efficient and accurate arbitrary-shaped text detector, termed Pixel Aggregation Network (PAN), which is equipped with a low computational-cost segmentation head and a learnable post-processing.

Scene Text Detection Segmentation +1

TACNet: Transition-Aware Context Network for Spatio-Temporal Action Detection

no code implementations CVPR 2019 Lin Song, Shiwei Zhang, Gang Yu, Hongbin Sun

In this paper, we define these ambiguous samples as "transitional states", and propose a Transition-Aware Context Network (TACNet) to distinguish transitional states.

Action Detection

ThunderNet: Towards Real-time Generic Object Detection

3 code implementations28 Mar 2019 Zheng Qin, Zeming Li, Zhaoning Zhang, Yiping Bao, Gang Yu, Yuxing Peng, Jian Sun

In this paper, we investigate the effectiveness of two-stage detectors in real-time generic detection and propose a lightweight two-stage detector named ThunderNet.

object-detection Object Detection

Shape Robust Text Detection with Progressive Scale Expansion Network

17 code implementations CVPR 2019 Wenhai Wang, Enze Xie, Xiang Li, Wenbo Hou, Tong Lu, Gang Yu, Shuai Shao

Due to the fact that there are large geometrical margins among the minimal scale kernels, our method is effective to split the close text instances, making it easier to use segmentation-based methods to detect arbitrary-shaped text instances.

Optical Character Recognition (OCR) Scene Text Detection +1

An End-to-End Network for Panoptic Segmentation

no code implementations CVPR 2019 Huanyu Liu, Chao Peng, Changqian Yu, Jingbo Wang, Xu Liu, Gang Yu, Wei Jiang

Panoptic segmentation, which needs to assign a category label to each pixel and segment each object instance simultaneously, is a challenging topic.

Panoptic Segmentation Segmentation

Scene Text Detection with Supervised Pyramid Context Network

2 code implementations21 Nov 2018 Enze Xie, Yuhang Zang, Shuai Shao, Gang Yu, Cong Yao, Guangyao Li

We propose a supervised pyramid context network (SPCNET) to precisely locate text regions while suppressing false positives.

Instance Segmentation Scene Text Detection +2

Modeling Local Geometric Structure of 3D Point Clouds using Geo-CNN

2 code implementations CVPR 2019 Shiyi Lan, Ruichi Yu, Gang Yu, Larry S. Davis

This encourages the network to preserve the geometric structure in Euclidean space throughout the feature extraction hierarchy.

Modeling Local Geometric Structure

Associating Inter-Image Salient Instances for Weakly Supervised Semantic Segmentation

no code implementations ECCV 2018 Ruochen Fan, Qibin Hou, Ming-Ming Cheng, Gang Yu, Ralph R. Martin, Shi-Min Hu

We also combine our method with Mask R-CNN for instance segmentation, and demonstrated for the first time the ability of weakly supervised instance segmentation using only keyword annotations.

Clustering graph partitioning +6

DetNet: Design Backbone for Object Detection

no code implementations ECCV 2018 Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun

(1) Recent object detectors like FPN and RetinaNet usually involve extra stages against the task of image classification to handle the objects with various scales.

Classification General Classification +6

CrowdHuman: A Benchmark for Detecting Human in a Crowd

1 code implementation30 Apr 2018 Shuai Shao, Zijian Zhao, Boxun Li, Tete Xiao, Gang Yu, Xiangyu Zhang, Jian Sun

There are a total of $470K$ human instances from the train and validation subsets, and $~22. 6$ persons per image, with various kinds of occlusions in the dataset.

Ranked #7 on Pedestrian Detection on Caltech (using extra training data)

Human Detection Object Detection +1

Learning a Discriminative Feature Network for Semantic Segmentation

3 code implementations CVPR 2018 Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang

Most existing methods of semantic segmentation still suffer from two aspects of challenges: intra-class inconsistency and inter-class indistinction.

Semantic Segmentation Thermal Image Segmentation

SFace: An Efficient Network for Face Detection in Large Scale Variations

no code implementations18 Apr 2018 Jianfeng Wang, Ye Yuan, Boxun Li, Gang Yu, Sun Jian

A new dataset called 4K-Face is also introduced to evaluate the performance of face detection with extreme large scale variations.

Face Detection Face Recognition

DetNet: A Backbone network for Object Detection

2 code implementations17 Apr 2018 Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun

Due to the gap between the image classification and object detection, we propose DetNet in this paper, which is a novel backbone network specifically designed for object detection.

Classification General Classification +6


no code implementations4 Dec 2017 Qizheng He, Jia-Nan Wu, Gang Yu, Chi Zhang

Another contribution is that we show with a deep learning based appearance model, it is easy to associate detections of the same object efficiently and also with high accuracy.

Multiple Object Tracking

Light-Head R-CNN: In Defense of Two-Stage Object Detector

5 code implementations20 Nov 2017 Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun

More importantly, simply replacing the backbone with a tiny network (e. g, Xception), our Light-Head R-CNN gets 30. 7 mmAP at 102 FPS on COCO, significantly outperforming the single-stage, fast detectors like YOLO and SSD on both speed and accuracy.

Vocal Bursts Valence Prediction

Face Attention Network: An Effective Face Detector for the Occluded Faces

1 code implementation20 Nov 2017 Jianfeng Wang, Ye Yuan, Gang Yu

The performance of face detection has been largely improved with the development of convolutional neural network.

Data Augmentation Occluded Face Detection

Cascaded Pyramid Network for Multi-Person Pose Estimation

5 code implementations CVPR 2018 Yilun Chen, Zhicheng Wang, Yuxiang Peng, Zhiqiang Zhang, Gang Yu, Jian Sun

In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which targets to relieve the problem from these "hard" keypoints.

Keypoint Detection Multi-Person Pose Estimation +1

MegDet: A Large Mini-Batch Object Detector

6 code implementations CVPR 2018 Chao Peng, Tete Xiao, Zeming Li, Yuning Jiang, Xiangyu Zhang, Kai Jia, Gang Yu, Jian Sun

The improvements in recent CNN-based object detection works, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from new network, new framework, or novel loss design.

object-detection Object Detection

Large Kernel Matters -- Improve Semantic Segmentation by Global Convolutional Network

2 code implementations CVPR 2017 Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, Jian Sun

One of recent trends [30, 31, 14] in network architec- ture design is stacking small filters (e. g., 1x1 or 3x3) in the entire network because the stacked small filters is more ef- ficient than a large kernel, given the same computational complexity.

Semantic Segmentation

Fast Action Proposals for Human Action Detection and Search

no code implementations CVPR 2015 Gang Yu, Junsong Yuan

Assuming each action is performed by a human with meaningful motion, both appearance and motion cues are utilized to measure the actionness of the video tubes.

Action Detection Video Segmentation +1

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