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Found 37 papers, 14 papers with code
On 3D Face Reconstruction via Cascaded Regression in Shape Space
Cascaded regression has been recently applied to reconstructing 3D faces from single 2D images directly in shape space, and achieved state-of-the-art performance.
Shape Recognition by Bag of Skeleton-associated Contour Parts
Contour and skeleton are two complementary representations for shape recognition.
Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition
Extensive experiments show that the proposed method can achieve the state-of-the-art accuracy in both face alignment and 3D face reconstruction, and benefit face recognition owing to its reconstructed PEN 3D face.
Disentangling Features in 3D Face Shapes for Joint Face Reconstruction and Recognition
This paper proposes an encoder-decoder network to disentangle shape features during 3D face reconstruction from single 2D images, such that the tasks of reconstructing accurate 3D face shapes and learning discriminative shape features for face recognition can be accomplished simultaneously.
Super-pixel cloud detection using Hierarchical Fusion CNN
Secondly, super-pixel level database is used to train our cloud detection models based on CNN and deep forest.
MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks
To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples.
Flexible Auto-weighted Local-coordinate Concept Factorization: A Robust Framework for Unsupervised Clustering
For auto-weighting, RFA-LCF jointly preserves the manifold structures in the basis concept space and new coordinate space in an adaptive manner by minimizing the reconstruction errors on clean data, anchor points and coordinates.
Zooming into Face Forensics: A Pixel-level Analysis
The stunning progress in face manipulation methods has made it possible to synthesize realistic fake face images, which poses potential threats to our society.
Theme-Matters: Fashion Compatibility Learning via Theme Attention
This model associates themes with the pairwise compatibility with attention, and thus compute the outfit-wise compatibility.
Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks
Inspired by the human "visual tracking" capability which leverages motion cues to distinguish the target from the background, we propose a Two-Stream Residual Convolutional Network (TS-RCN) for visual tracking, which successfully exploits both appearance and motion features for model update.
A survey of face recognition techniques under occlusion
As a part of this review, we introduce face detection under occlusion, a preliminary step in face recognition.
Semi-Siamese Training for Shallow Face Learning
Extensive experiments on various benchmarks of face recognition show the proposed method significantly improves the training, not only in shallow face learning, but also for conventional deep face data.
NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition
However, the correlation between hard positive and hard negative is overlooked, and so is the relation between the margins in positive and negative logits.
The Elements of End-to-end Deep Face Recognition: A Survey of Recent Advances
To start with, we present an overview of the end-to-end deep face recognition.
Neural Architecture Search for Joint Human Parsing and Pose Estimation
With the spirit of NAS, we propose to search for an efficient network architecture (NPPNet) to tackle two tasks at the same time.
Student Network Learning via Evolutionary Knowledge Distillation
Inspired by that, we propose an evolutionary knowledge distillation approach to improve the transfer effectiveness of teacher knowledge.
Towards NIR-VIS Masked Face Recognition
In this paper, we aim to address the challenge of NIR-VIS masked face recognition from the perspectives of training data and training method.
Multi-Agent Semi-Siamese Training for Long-tail and Shallow Face Learning
However, unlike the existing public face datasets, in many real-world scenarios of face recognition, the depth of training dataset is shallow, which means only two face images are available for each ID.
Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval
When encountering a dubious diagnostic case, medical instance retrieval can help radiologists make evidence-based diagnoses by finding images containing instances similar to a query case from a large image database.
Face2Exp: Combating Data Biases for Facial Expression Recognition
To combat the mismatch between FR and FER data, Meta-Face2Exp uses a circuit feedback mechanism, which improves the base network with the feedback from the adaptation network.
Trustable Co-label Learning from Multiple Noisy Annotators
This raises the following important question: how can we effectively use a small amount of trusted data to facilitate robust classifier learning from multiple annotators?
Adjacent Context Coordination Network for Salient Object Detection in Optical Remote Sensing Images
As the key component of ACCoNet, ACCoM activates the salient regions of output features of the encoder and transmits them to the decoder.
CaCo: Both Positive and Negative Samples are Directly Learnable via Cooperative-adversarial Contrastive Learning
It trains an encoder by distinguishing positive samples from negative ones given query anchors.
Ranked #65 on
Self-Supervised Image Classification
on ImageNet
Bootstrapping Multi-view Representations for Fake News Detection
Representations from each view are separately used to coarsely predict the fidelity of the whole news, and the multimodal representations are able to predict the cross-modal consistency.
Rank-Based Filter Pruning for Real-Time UAV Tracking
Model compression is a promising way to narrow the gap (i. e., effciency, precision) between DCF- and deep learning- based trackers, which has not caught much attention in UAV tracking.
Deepfake Video Detection with Spatiotemporal Dropout Transformer
Existing image-level approaches often focus on single frame and ignore the spatiotemporal cues hidden in deepfake videos, resulting in poor generalization and robustness.
SuperVessel: Segmenting High-resolution Vessel from Low-resolution Retinal Image
Vascular segmentation extracts blood vessels from images and serves as the basis for diagnosing various diseases, like ophthalmic diseases.
DPIT: Dual-Pipeline Integrated Transformer for Human Pose Estimation
Human pose estimation aims to figure out the keypoints of all people in different scenes.
Ranked #22 on
Pose Estimation
on COCO test-dev
Scale Attention for Learning Deep Face Representation: A Study Against Visual Scale Variation
Such multi-shot scheme brings inference burden, and the predefined scales inevitably have gap from real data.
RGB-T Semantic Segmentation with Location, Activation, and Sharpening
The highlight of LASNet is that we fully consider the characteristics of cross-modal features at different levels, and accordingly propose three specific modules for better segmentation.
Ranked #26 on
Thermal Image Segmentation
on MFN Dataset
Adaptive and Background-Aware Vision Transformer for Real-Time UAV Tracking
In this paper, we propose an efficient ViT-based tracking framework, Aba-ViTrack, for UAV tracking.
Towards Discriminative Representations with Contrastive Instances for Real-Time UAV Tracking
Lightweight Deep learning (DL)-based trackers can achieve a good balance between efficiency and precision but performance gains are limited by the compression rate.
Coupled Confusion Correction: Learning from Crowds with Sparse Annotations
Moreover, we cluster the ``annotator groups'' who share similar expertise so that their confusion matrices could be corrected together.
M3D: Dataset Condensation by Minimizing Maximum Mean Discrepancy
Nowadays, optimization-oriented methods have been the primary method in the field of dataset condensation for achieving SOTA results.
Fact-checking based fake news detection: a review
This paper reviews and summarizes the research results on fact-based fake news from the perspectives of tasks and problems, algorithm strategies, and datasets.
Harnessing Intra-group Variations Via a Population-Level Context for Pathology Detection
Realizing sufficient separability between the distributions of healthy and pathological samples is a critical obstacle for pathology detection convolutional models.
DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Prediction
In Multiple Object Tracking, objects often exhibit non-linear motion of acceleration and deceleration, with irregular direction changes.
