32 citations · 230 across the 25 of their papers we have counts for
25 papers
STC: Spatio-Temporal Contrastive Learning for Video Instance Segmentation
Zhengkai Jiang, Zhangxuan Gu, Jinlong Peng +6
Video Instance Segmentation (VIS) is a task that simultaneously requires classification, segmentation, and instance association in a video. Recent VIS approaches rely on sophistica…
ASFD: Automatic and Scalable Face Detector
Jian Li, Bin Zhang, Yabiao Wang +6
Along with current multi-scale based detectors, Feature Aggregation and Enhancement (FAE) modules have shown superior performance gains for cutting-edge object detection. However,…
LCTR: On Awakening the Local Continuity of Transformer for Weakly Supervised Object Localization
Zhiwei Chen, Changan Wang, Yabiao Wang +6
Weakly supervised object localization (WSOL) aims to learn object localizer solely by using image-level labels. The convolution neural network (CNN) based techniques often result i…
Ranking Distance Calibration for Cross-Domain Few-Shot Learning
Pan Li, Shaogang Gong, Chengjie Wang +1
Recent progress in few-shot learning promotes a more realistic cross-domain setting, where the source and target datasets are from different domains. Due to the domain gap and disj…
LSTC: Boosting Atomic Action Detection with Long-Short-Term Context
Yuxi Li, Boshen Zhang, Jian Li +5
In this paper, we place the atomic action detection problem into a Long-Short Term Context (LSTC) to analyze how the temporal reliance among video signals affect the action detecti…
Rethinking Counting and Localization in Crowds:A Purely Point-Based Framework
Qingyu Song, Changan Wang, Zhengkai Jiang +6
Localizing individuals in crowds is more in accordance with the practical demands of subsequent high-level crowd analysis tasks than simply counting. However, existing localization…
Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting
Changan Wang, Qingyu Song, Boshen Zhang +7
Recently, the problem of inaccurate learning targets in crowd counting draws increasing attention. Inspired by a few pioneering work, we solve this problem by trying to predict the…
SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking
Jinlong Peng, Zhengkai Jiang, Yueyang Gu +5
Recently, most siamese network based trackers locate targets via object classification and bounding-box regression. Generally, they select the bounding-box with maximum classificat…
Learning Dynamic Alignment via Meta-filter for Few-shot Learning
Chengming Xu, Chen Liu, Li Zhang +5
Few-shot learning (FSL), which aims to recognise new classes by adapting the learned knowledge with extremely limited few-shot (support) examples, remains an important open problem…
Learning Salient Boundary Feature for Anchor-free Temporal Action Localization
Chuming Lin, Chengming Xu, Donghao Luo +6
Temporal action localization is an important yet challenging task in video understanding. Typically, such a task aims at inferring both the action category and localization of the…
Learning Comprehensive Motion Representation for Action Recognition
Mingyu Wu, Boyuan Jiang, Donghao Luo +7
For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame. Recent efforts at…
Aurora Guard: Reliable Face Anti-Spoofing via Mobile Lighting System
Jian Zhang, Ying Tai, Taiping Yao +6
Face authentication on mobile end has been widely applied in various scenarios. Despite the increasing reliability of cutting-edge face authentication/verification systems to varia…
Frequency Consistent Adaptation for Real World Super Resolution
Xiaozhong Ji, Guangpin Tao, Yun Cao +5
Recent deep-learning based Super-Resolution (SR) methods have achieved remarkable performance on images with known degradation. However, these methods always fail in real-world sce…
Adversarial Refinement Network for Human Motion Prediction
Xianjin Chao, Yanrui Bin, Wenqing Chu +6
Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward dee…
Adversarial Semantic Data Augmentation for Human Pose Estimation
Yanrui Bin, Xuan Cao, Xinya Chen +7
Human pose estimation is the task of localizing body keypoints from still images. The state-of-the-art methods suffer from insufficient examples of challenging cases such as symmet…
Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking
Jinlong Peng, Changan Wang, Fangbin Wan +7
Existing Multiple-Object Tracking (MOT) methods either follow the tracking-by-detection paradigm to conduct object detection, feature extraction and data association separately, or…
Temporal Distinct Representation Learning for Action Recognition
Junwu Weng, Donghao Luo, Yabiao Wang +6
Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos. However…
ACFD: Asymmetric Cartoon Face Detector
Bin Zhang, Jian Li, Yabiao Wang +5
Cartoon face detection is a more challenging task than human face detection due to many difficult scenarios is involved. Aiming at the characteristics of cartoon faces, such as hug…
Dense Scene Multiple Object Tracking with Box-Plane Matching
Jinlong Peng, Yueyang Gu, Yabiao Wang +3
Multiple Object Tracking (MOT) is an important task in computer vision. MOT is still challenging due to the occlusion problem, especially in dense scenes. Following the tracking-by…
ASFD: Automatic and Scalable Face Detector
Bin Zhang, Jian Li, Yabiao Wang +7
In this paper, we propose a novel Automatic and Scalable Face Detector (ASFD), which is based on a combination of neural architecture search techniques as well as a new loss design…
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…
Fast Learning of Temporal Action Proposal via Dense Boundary Generator
Chuming Lin, Jian Li, Yabiao Wang +7
Generating temporal action proposals remains a very challenging problem, where the main issue lies in predicting precise temporal proposal boundaries and reliable action confidence…
Anti-Confusing: Region-Aware Network for Human Pose Estimation
Xuan Cao, Yanhao Ge, Ying Tai +5
In this work, we propose a novel framework named Region-Aware Network (RANet), which learns the ability of anti-confusing in case of heavy occlusion, nearby person and symmetric ap…
Aurora Guard: Real-Time Face Anti-Spoofing via Light Reflection
Yao Liu, Ying Tai, Jilin Li +6
In this paper, we propose a light reflection based face anti-spoofing method named Aurora Guard (AG), which is fast, simple yet effective that has already been deployed in real-wor…