Papers Face Hallucination
“Face Hallucination” 태그가 달린 논문 53편 · 필터 해제
Self-Captioning Multimodal Interaction Tuning: Amplifying Exploitable Redundancies for Robust Vision Language Models
Current vision language models face hallucination and robustness issues against ambiguous or corrupted modalities. We hypothesize that these issues can be addressed by exploiting the shared information between modalities…
Face HallucinationVisual GroundingSupervision-by-Hallucination-and-Transfer: A Weakly-Supervised Approach for Robust and Precise Facial Landmark Detection
High-precision facial landmark detection (FLD) relies on high-resolution deep feature representations. However, low-resolution face images or the compression (via pooling or strided convolution) of originally high-resolu…
Facial Landmark DetectionFace HallucinationPose TransferAudio-visual video face hallucination with frequency supervision and cross modality support by speech based lip reading loss
Recently, there has been numerous breakthroughs in face hallucination tasks. However, the task remains rather challenging in videos in comparison to the images due to inherent consistency issues. The presence of extra te…
Face HallucinationGenerative Adversarial NetworkHallucinationLip ReadingEscaping Data Scarcity for High-Resolution Heterogeneous Face Hallucination
In Heterogeneous Face Recognition (HFR), the objective is to match faces across two different domains such as visible and thermal. Large domain discrepancy makes HFR a difficult problem. Recent methods attempting to fill…
Face GenerationFace HallucinationFace RecognitionFederated Learning+3GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors
Face image super resolution (face hallucination) usually relies on facial priors to restore realistic details and preserve identity information. Recent advances can achieve impressive results with the help of GAN prior. …
Face HallucinationHallucinationImage Super-ResolutionSuper-ResolutionIdentity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior
Over the past few decades, numerous attempts have been made to address the problem of recovering a high-resolution (HR) facial image from its corresponding low-resolution (LR) counterpart, a task commonly referred to as …
3D Face ReconstructionFace HallucinationFace ReconstructionHallucination+1AGA-GAN: Attribute Guided Attention Generative Adversarial Network with U-Net for Face Hallucination
The performance of facial super-resolution methods relies on their ability to recover facial structures and salient features effectively. Even though the convolutional neural network and generative adversarial network-ba…
AttributeFace HallucinationGenerative Adversarial NetworkHallucination+1EDFace-Celeb-1M: Benchmarking Face Hallucination with a Million-scale Dataset
Recent deep face hallucination methods show stunning performance in super-resolving severely degraded facial images, even surpassing human ability. However, these algorithms are mainly evaluated on non-public synthetic d…
BenchmarkingFace HallucinationHallucinationImage Super-ResolutionFrequency Aware Face Hallucination Generative Adversarial Network with Semantic Structural Constraint
In this paper, we address the issue of face hallucination. Most current face hallucination methods rely on two-dimensional facial priors to generate high resolution face images from low resolution face images. These meth…
Face HallucinationGenerative Adversarial NetworkHallucinationLR-to-HR Face Hallucination with an Adversarial Progressive Attribute-Induced Network
Face super-resolution is a challenging and highly ill-posed problem since a low-resolution (LR) face image may correspond to multiple high-resolution (HR) ones during the hallucination process and cause a dramatic identi…
AttributeFace HallucinationHallucinationSuper-ResolutionPro-UIGAN: Progressive Face Hallucination from Occluded Thumbnails
In this paper, we study the task of hallucinating an authentic high-resolution (HR) face from an occluded thumbnail. We propose a multi-stage Progressive Upsampling and Inpainting Generative Adversarial Network, dubbed P…
Face AlignmentFace HallucinationFace ParsingFace Recognition+23D human tongue reconstruction from single "in-the-wild" images
3D face reconstruction from a single image is a task that has garnered increased interest in the Computer Vision community, especially due to its broad use in a number of applications such as realistic 3D avatar creation…
3D Face ReconstructionFace HallucinationFace RecognitionFace Reconstruction+2VidFace: A Full-Transformer Solver for Video FaceHallucination with Unaligned Tiny Snapshots
In this paper, we investigate the task of hallucinating an authentic high-resolution (HR) human face from multiple low-resolution (LR) video snapshots. We propose a pure transformer-based model, dubbed VidFace, to fully …
Face HallucinationHallucinationSimultaneous Face Hallucination and Translation for Thermal to Visible Face Verification using Axial-GAN
Existing thermal-to-visible face verification approaches expect the thermal and visible face images to be of similar resolution. This is unlikely in real-world long-range surveillance systems, since humans are distant fr…
Face HallucinationFace VerificationGenerative Adversarial NetworkHallucination+1Deep Learning-based Face Super-Resolution: A Survey
Face super-resolution (FSR), also known as face hallucination, which is aimed at enhancing the resolution of low-resolution (LR) face images to generate high-resolution (HR) face images, is a domain-specific image super-…
Deep LearningFace HallucinationHallucinationImage Super-Resolution+2Face Hallucination via Split-Attention in Split-Attention Network
Recently, convolutional neural networks (CNNs) have been widely employed to promote the face hallucination due to the ability to predict high-frequency details from a large number of samples. However, most of them fail t…
Face DetectionFace HallucinationFace RecognitionHallucination+2HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
Existing face restoration researches typically relies on either the degradation prior or explicit guidance labels for training, which often results in limited generalization ability over real-world images with heterogene…
Blind Face RestorationFace HallucinationImage DenoisingImage Restoration+1DeepSEE: Deep Disentangled Semantic Explorative Extreme Super-Resolution
Super-resolution (SR) is by definition ill-posed. There are infinitely many plausible high-resolution variants for a given low-resolution natural image. Most of the current literature aims at a single deterministic solut…
Face HallucinationSuper-ResolutionPULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
The primary aim of single-image super-resolution is to construct high-resolution (HR) images from corresponding low-resolution (LR) inputs. In previous approaches, which have generally been supervised, the training objec…
Face HallucinationHallucinationImage Super-ResolutionSuper-ResolutionCopy and Paste GAN: Face Hallucination from Shaded Thumbnails
Existing face hallucination methods based on convolutional neural networks (CNN) have achieved impressive performance on low-resolution (LR) faces in a normal illumination condition. However, their performance degrades d…
Face HallucinationGenerative Adversarial NetworkHallucination