80 citations · 140 across the 34 of their papers we have counts for
30 papers · 1 filter
LPM 1.0: Video-based Character Performance Model
Ailing Zeng, Casper Yang, Chauncey Ge +22
Performance, the externalization of intent, emotion, and personality through visual, vocal, and temporal behavior, is what makes a character alive. Learning such performance from v…
DriveCombo: Benchmarking Compositional Traffic Rule Reasoning in Autonomous Driving
Enhui Ma, Jiahuan Zhang, Guantian Zheng +10
Multimodal Large Language Models (MLLMs) are rapidly becoming the intelligence brain of end-to-end autonomous driving systems. A key challenge is to assess whether MLLMs can truly…
OT-ALD: Aligning Latent Distributions with Optimal Transport for Accelerated Image-to-Image Translation
Zhanpeng Wang, Shuting Cao, Yuhang Lu +3
The Dual Diffusion Implicit Bridge (DDIB) is an emerging image-to-image (I2I) translation method that preserves cycle consistency while achieving strong flexibility. It links two i…
Pose-invariant face recognition via feature-space pose frontalization
Nikolay Stanishev, Yuhang Lu, Touradj Ebrahimi
Pose-invariant face recognition has become a challenging problem for modern AI-based face recognition systems. It aims at matching a profile face captured in the wild with a fronta…
Can LVLMs Obtain a Driver's License? A Benchmark Towards Reliable AGI for Autonomous Driving
Yuhang Lu, Yichen Yao, Jiadong Tu +3
Large Vision-Language Models (LVLMs) have recently garnered significant attention, with many efforts aimed at harnessing their general knowledge to enhance the interpretability and…
RenderWorld: World Model with Self-Supervised 3D Label
Ziyang Yan, Wenzhen Dong, Yihua Shao +8
End-to-end autonomous driving with vision-only is not only more cost-effective compared to LiDAR-vision fusion but also more reliable than traditional methods. To achieve a economi…
Towards A Comprehensive Visual Saliency Explanation Framework for AI-based Face Recognition Systems
Yuhang Lu, Zewei Xu, Touradj Ebrahimi
Over recent years, deep convolutional neural networks have significantly advanced the field of face recognition techniques for both verification and identification purposes. Despit…
Explainable Face Verification via Feature-Guided Gradient Backpropagation
Yuhang Lu, Zewei Xu, Touradj Ebrahimi
Recent years have witnessed significant advancement in face recognition (FR) techniques, with their applications widely spread in people's lives and security-sensitive areas. There…
Towards the Detection of AI-Synthesized Human Face Images
Yuhang Lu, Touradj Ebrahimi
Over the past years, image generation and manipulation have achieved remarkable progress due to the rapid development of generative AI based on deep learning. Recent studies have d…
OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queries
Yuhang Lu, Xinge Zhu, Tai Wang +1
Occupancy prediction has increasingly garnered attention in recent years for its fine-grained understanding of 3D scenes. Traditional approaches typically rely on dense, regular gr…
See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data
Yuhang Lu, Qi Jiang, Runnan Chen +3
Zero-shot point cloud segmentation aims to make deep models capable of recognizing novel objects in point cloud that are unseen in the training phase. Recent trends favor the pipel…
Discriminative Deep Feature Visualization for Explainable Face Recognition
Zewei Xu, Yuhang Lu, Touradj Ebrahimi
Despite the huge success of deep convolutional neural networks in face recognition (FR) tasks, current methods lack explainability for their predictions because of their "black-box…
Towards Visual Saliency Explanations of Face Verification
Yuhang Lu, Zewei Xu, Touradj Ebrahimi
In the past years, deep convolutional neural networks have been pushing the frontier of face recognition (FR) techniques in both verification and identification scenarios. Despite…
Assessment Framework for Deepfake Detection in Real-world Situations
Yuhang Lu, Touradj Ebrahimi
Detecting digital face manipulation in images and video has attracted extensive attention due to the potential risk to public trust. To counteract the malicious usage of such techn…
Explanation of Face Recognition via Saliency Maps
Yuhang Lu, Touradj Ebrahimi
Despite the significant progress in face recognition in the past years, they are often treated as "black boxes" and have been criticized for lacking explainability. It becomes incr…
Impact of Video Processing Operations in Deepfake Detection
Yuhang Lu, Touradj Ebrahimi
The detection of digital face manipulation in video has attracted extensive attention due to the increased risk to public trust. To counteract the malicious usage of such technique…
Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation
Yuhang Lu, Touradj Ebrahimi
Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution g…
Semi-supervised Deep Large-baseline Homography Estimation with Progressive Equivalence Constraint
Hai Jiang, Haipeng Li, Yuhang Lu +2
Homography estimation is erroneous in the case of large-baseline due to the low image overlay and limited receptive field. To address it, we propose a progressive estimation strate…
Cross-domain Few-shot Segmentation with Transductive Fine-tuning
Yuhang Lu, Xinyi Wu, Zhenyao Wu +1
Few-shot segmentation (FSS) expects models trained on base classes to work on novel classes with the help of a few support images. However, when there exists a domain gap between t…
Unsupervised Homography Estimation with Coplanarity-Aware GAN
Mingbo Hong, Yuhang Lu, Nianjin Ye +3
Estimating homography from an image pair is a fundamental problem in image alignment. Unsupervised learning methods have received increasing attention in this field due to their pr…
A New Approach to Improve Learning-based Deepfake Detection in Realistic Conditions
Yuhang Lu, Touradj Ebrahimi
Deep convolutional neural networks have achieved exceptional results on multiple detection and recognition tasks. However, the performance of such detectors are often evaluated in…
A Novel Framework for Assessment of Learning-based Detectors in Realistic Conditions with Application to Deepfake Detection
Yuhang Lu, Ruizhi Luo, Touradj Ebrahimi
Deep convolutional neural networks have shown remarkable results on multiple detection tasks. Despite the significant progress, the performance of such detectors are often assessed…
Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Semantic Segmentation
Xinyi Wu, Zhenyao Wu, Yuhang Lu +2
In this paper, we tackle the problem of one-shot unsupervised domain adaptation (OSUDA) for semantic segmentation where the segmentors only see one unlabeled target image during tr…
Impact of Benign Modifications on Discriminative Performance of Deepfake Detectors
Yuhang Lu, Evgeniy Upenik, Touradj Ebrahimi
Deepfakes are becoming increasingly popular in both good faith applications such as in entertainment and maliciously intended manipulations such as in image and video forgery. Prim…