3 papers
cs.CV2026
DiveUp: Learning Feature Upsampling from Diverse Vision Foundation Models
Xiaoqiong Liu, Heng Fan
Recently, feature upsampling has gained increasing attention owing to its effectiveness in enhancing vision foundation models (VFMs) for pixel-level understanding tasks. Existing m…
cs.CV2024
Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance
Liting Lin, Heng Fan, Zhipeng Zhang +3
Motivated by the Parameter-Efficient Fine-Tuning (PEFT) in large language models, we propose LoRAT, a method that unveils the power of large ViT model for tracking within laborator…
cs.CV2024
Cyclic Refiner: Object-Aware Temporal Representation Learning for Multi-View 3D Detection and Tracking
Mingzhe Guo, Zhipeng Zhang, Liping Jing +3
We propose a unified object-aware temporal learning framework for multi-view 3D detection and tracking tasks. Having observed that the efficacy of the temporal fusion strategy in r…