6 papers
UniPAR: A Unified Framework for Pedestrian Attribute Recognition
Minghe Xu, Rouying Wu, Jiarui Xu +5
Pedestrian Attribute Recognition is a foundational computer vision task that provides essential support for downstream applications, including person retrieval in video surveillanc…
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal +9
Self-attention performs well in long context but has quadratic complexity. Existing RNN layers have linear complexity, but their performance in long context is limited by the expre…
One-Minute Video Generation with Test-Time Training
Karan Dalal, Daniel Koceja, Gashon Hussein +12
Transformers today still struggle to generate one-minute videos because self-attention layers are inefficient for long context. Alternatives such as Mamba layers struggle with comp…
LoRA-TTT: Low-Rank Test-Time Training for Vision-Language Models
Yuto Kojima, Jiarui Xu, Xueyan Zou +1
The rapid advancements in vision-language models (VLMs), such as CLIP, have intensified the need to address distribution shifts between training and testing datasets. Although prio…
Parallel Sequence Modeling via Generalized Spatial Propagation Network
Hongjun Wang, Wonmin Byeon, Jiarui Xu +6
We present the Generalized Spatial Propagation Network (GSPN), a new attention mechanism optimized for vision tasks that inherently captures 2D spatial structures. Existing attenti…
HandsOnVLM: Vision-Language Models for Hand-Object Interaction Prediction
Chen Bao, Jiarui Xu, Xiaolong Wang +2
How can we predict future interaction trajectories of human hands in a scene given high-level colloquial task specifications in the form of natural language? In this paper, we exte…