9 papers · 1 filter
Beyond Facial Consistency: Personalized Person Image Generation with Holistic Identity Preservation
Yuxuan Xiao, Shanshan Zhang, Jian Yang +1
Personalized person image generation requires preserving subject identity across both local facial details and broader appearance cues. Existing methods typically emphasize only on…
IREU: Identity-Related Encoder-Only Unlearning for Customized Portrait Generation
Chaoyi Shi, Shanshan Zhang, Jian Yang
Customized Portrait Generation (CPG) technologies have been widely used to generate high-fidelity person images given an input image indicating the identity and a text prompt indic…
One-Shot Novel View and Pose Human Image Synthesis via 3D Prior Guided Diffusion Model
Shenjian Gong, Kangkan Wang, Shanshan Zhang +1
This paper addresses the challenge of one-shot novel view and pose human image synthesis. The existing methods transfer the reference human image to a target pose using a set of 2D…
Revisiting Token Compression for Accelerating ViT-based Sparse Multi-View 3D Object Detectors
Mingqian Ji, Shanshan Zhang, Jian Yang
Vision Transformer (ViT)-based sparse multi-view 3D object detectors have achieved remarkable accuracy but still suffer from high inference latency due to heavy token processing. T…
RayMamba: Ray-Aligned Serialization for Long-Range 3D Object Detection
Cheng Lu, Mingqian Ji, Shanshan Zhang +2
Long-range 3D object detection remains challenging because LiDAR observations become highly sparse and fragmented in the far field, making reliable context modeling difficult for e…
Enhancing Pseudo-Boxes via Data-Level LiDAR-Camera Fusion for Unsupervised 3D Object Detection
Mingqian Ji, Jian Yang, Shanshan Zhang
Existing LiDAR-based 3D object detectors typically rely on manually annotated labels for training to achieve good performance. However, obtaining high-quality 3D labels is time-con…
OcRFDet: Object-Centric Radiance Fields for Multi-View 3D Object Detection in Autonomous Driving
Mingqian Ji, Jian Yang, Shanshan Zhang
Current multi-view 3D object detection methods typically transfer 2D features into 3D space using depth estimation or 3D position encoder, but in a fully data-driven and implicit m…
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection
Mingqian Ji, Jian Yang, Shanshan Zhang
State-of-the-art LiDAR-camera 3D object detectors usually focus on feature fusion. However, they neglect the factor of depth while designing the fusion strategy. In this work, we a…
Imagine the Unseen: Occluded Pedestrian Detection via Adversarial Feature Completion
Shanshan Zhang, Mingqian Ji, Yang Li +1
Pedestrian detection has significantly progressed in recent years, thanks to the development of DNNs. However, detection performance at occluded scenes is still far from satisfacto…