2 citations · 6 across the 20 of their papers we have counts for
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Fusion-then-Distillation: Toward Cross-modal Positive Distillation for Domain Adaptive 3D Semantic Segmentation
Yao Wu, Mingwei Xing, Yachao Zhang +2
In cross-modal unsupervised domain adaptation, a model trained on source-domain data (e.g., synthetic) is adapted to target-domain data (e.g., real-world) without access to target…
Large Continual Instruction Assistant
Jingyang Qiao, Zhizhong Zhang, Xin Tan +3
Continual Instruction Tuning (CIT) is adopted to continually instruct Large Models to follow human intent data by data. It is observed that existing gradient update would heavily d…
Data-free Distillation with Degradation-prompt Diffusion for Multi-weather Image Restoration
Pei Wang, Xiaotong Luo, Yuan Xie +1
Multi-weather image restoration has witnessed incredible progress, while the increasing model capacity and expensive data acquisition impair its applications in memory-limited devi…
Mutual Information Guided Optimal Transport for Unsupervised Visible-Infrared Person Re-identification
Zhizhong Zhang, Jiangming Wang, Xin Tan +4
Unsupervised visible infrared person re-identification (USVI-ReID) is a challenging retrieval task that aims to retrieve cross-modality pedestrian images without using any label in…
Exploring the Untouched Sweeps for Conflict-Aware 3D Segmentation Pretraining
Tianfang Sun, Zhizhong Zhang, Xin Tan +2
LiDAR-camera 3D representation pretraining has shown significant promise for 3D perception tasks and related applications. However, two issues widely exist in this framework: 1) So…
Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception
Haoming Chen, Zhizhong Zhang, Yanyun Qu +3
An effective pre-training framework with universal 3D representations is extremely desired in perceiving large-scale dynamic scenes. However, establishing such an ideal framework t…
Robust Pseudo-label Learning with Neighbor Relation for Unsupervised Visible-Infrared Person Re-Identification
Xiangbo Yin, Jiangming Shi, Yachao Zhang +4
Unsupervised Visible-Infrared Person Re-identification (USVI-ReID) presents a formidable challenge, which aims to match pedestrian images across visible and infrared modalities wit…
Gradient Projection For Continual Parameter-Efficient Tuning
Jingyang Qiao, Zhizhong Zhang, Xin Tan +4
Parameter-efficient tunings (PETs) have demonstrated impressive performance and promising perspectives in training large models, while they are still confronted with a common probl…
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection
Xiaofan Li, Zhizhong Zhang, Xin Tan +4
The vision-language model has brought great improvement to few-shot industrial anomaly detection, which usually needs to design of hundreds of prompts through prompt engineering. F…
Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification
Jiangming Shi, Xiangbo Yin, Yachao Zhang +3
Unsupervised visible-infrared person re-identification (USVI-ReID) aims to match specified people in infrared images to visible images without annotations, and vice versa. USVI-ReI…
Multi-Memory Matching for Unsupervised Visible-Infrared Person Re-Identification
Jiangming Shi, Xiangbo Yin, Yeyun Chen +4
Unsupervised visible-infrared person re-identification (USL-VI-ReID) is a promising yet challenging retrieval task. The key challenges in USL-VI-ReID are to effectively generate ps…