Search Results for author: Can Zhang

Found 17 papers, 7 papers with code

Indeterminate Probability Neural Network

1 code implementation21 Mar 2023 Tao Yang, Chuang Liu, Xiaofeng Ma, Weijia Lu, Ning Wu, Bingyang Li, Zhifei Yang, Peng Liu, Lin Sun, Xiaodong Zhang, Can Zhang

Besides, for our proposed neural network framework, the output of neural network is defined as probability events, and based on the statistical analysis of these events, the inference model for classification task is deduced.


LocVTP: Video-Text Pre-training for Temporal Localization

1 code implementation21 Jul 2022 Meng Cao, Tianyu Yang, Junwu Weng, Can Zhang, Jue Wang, Yuexian Zou

To further enhance the temporal reasoning ability of the learned feature, we propose a context projection head and a temporal aware contrastive loss to perceive the contextual relationships.

Retrieval Temporal Localization +1

CA-UDA: Class-Aware Unsupervised Domain Adaptation with Optimal Assignment and Pseudo-Label Refinement

no code implementations26 May 2022 Can Zhang, Gim Hee Lee

However, source domain bias that deteriorates the pseudo-labels can still exist since the shared network of the source and target domains are typically used for the pseudo-label selections.

Image Classification Pseudo Label +1

SpatioTemporal Focus for Skeleton-based Action Recognition

no code implementations31 Mar 2022 Liyu Wu, Can Zhang, Yuexian Zou

Inspired by the recent attention mechanism, we propose a multi-grain contextual focus module, termed MCF, to capture the action associated relation information from the body joints and parts.

Action Recognition Skeleton Based Action Recognition

Unsupervised Pre-training for Temporal Action Localization Tasks

1 code implementation CVPR 2022 Can Zhang, Tianyu Yang, Junwu Weng, Meng Cao, Jue Wang, Yuexian Zou

These pre-trained models can be sub-optimal for temporal localization tasks due to the inherent discrepancy between video-level classification and clip-level localization.

Contrastive Learning Representation Learning +4

MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction

no code implementations30 Nov 2021 Wei Guo, Can Zhang, ZhiCheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang

With the help of two novel CNN-based multi-interest extractors, self-supervision signals are discovered with full considerations of different interest representations (point-wise and union-wise), interest dependencies (short-range and long-range), and interest correlations (inter-item and intra-item).

Click-Through Rate Prediction Contrastive Learning +3

On Pursuit of Designing Multi-modal Transformer for Video Grounding

no code implementations EMNLP 2021 Meng Cao, Long Chen, Mike Zheng Shou, Can Zhang, Yuexian Zou

Almost all existing video grounding methods fall into two frameworks: 1) Top-down model: It predefines a set of segment candidates and then conducts segment classification and regression.

Video Grounding

Long-Short Temporal Modeling for Efficient Action Recognition

no code implementations30 Jun 2021 Liyu Wu, Yuexian Zou, Can Zhang

Efficient long-short temporal modeling is key for enhancing the performance of action recognition task.

Action Recognition

SRF-Net: Selective Receptive Field Network for Anchor-Free Temporal Action Detection

no code implementations29 Jun 2021 Ranyu Ning, Can Zhang, Yuexian Zou

Current mainstream one-stage TAD approaches localize and classify action proposals relying on pre-defined anchors, where the location and scale for action instances are set by designers.

Action Detection

All You Need is a Second Look: Towards Arbitrary-Shaped Text Detection

no code implementations24 Jun 2021 Meng Cao, Can Zhang, Dongming Yang, Yuexian Zou

Compared to the traditional single-stage segmentation network, our NASK conducts the detection in a coarse-to-fine manner with the first stage segmentation spotting the rectangle text proposals and the second one retrieving compact representations.

Instance Segmentation Semantic Segmentation

RR-Net: Injecting Interactive Semantics in Human-Object Interaction Detection

no code implementations30 Apr 2021 Dongming Yang, Yuexian Zou, Can Zhang, Meng Cao, Jie Chen

Upon the frame, an Interaction Intensifier Module and a Correlation Parsing Module are carefully designed, where: a) interactive semantics from humans can be exploited and passed to objects to intensify interactions, b) interactive correlations among humans, objects and interactions are integrated to promote predictions.

Human-Object Interaction Detection

CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning

1 code implementation CVPR 2021 Can Zhang, Meng Cao, Dongming Yang, Jie Chen, Yuexian Zou

In this paper, we argue that learning by comparing helps identify these hard snippets and we propose to utilize snippet Contrastive learning to Localize Actions, CoLA for short.

CoLA Contrastive Learning +3

Multi-Scale Cascading Network with Compact Feature Learning for RGB-Infrared Person Re-Identification

no code implementations12 Dec 2020 Can Zhang, Hong Liu, Wei Guo, Mang Ye

RGB-Infrared person re-identification (RGB-IR Re-ID) aims to match persons from heterogeneous images captured by visible and thermal cameras, which is of great significance in the surveillance system under poor light conditions.

Person Re-Identification

Non-Autoregressive Coarse-to-Fine Video Captioning

1 code implementation27 Nov 2019 Bang Yang, Yuexian Zou, Fenglin Liu, Can Zhang

However, mainstream video captioning methods suffer from slow inference speed due to the sequential manner of autoregressive decoding, and prefer generating generic descriptions due to the insufficient training of visual words (e. g., nouns and verbs) and inadequate decoding paradigm.

Video Captioning

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