11 citations · 21 across the 5 of their papers we have counts for
5 papers
Lightweight and Generalizable Multi-Sensor Human Activity Recognition via Cascaded Fusion and Style-Augmented Decomposition
Wang Chenglong, Zhuo Yan, Ding Wenbo +1
Wearable Human Activity Recognition (WHAR) is a prominent research area within ubiquitous computing, whose core lies in effectively modeling intra- and inter-sensor spatio-temporal…
LLMs can see and hear without any training
Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen +2
We present MILS: Multimodal Iterative LLM Solver, a surprisingly simple, training-free approach, to imbue multimodal capabilities into your favorite LLM. Leveraging their innate ab…
Learning Video Representations without Natural Videos
Xueyang Yu, Xinlei Chen, Yossi Gandelsman
We show that useful video representations can be learned from synthetic videos and natural images, without incorporating natural videos in the training. We propose a progression of…
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels
Duy-Kien Nguyen, Mahmoud Assran, Unnat Jain +3
This work does not introduce a new method. Instead, we present an interesting finding that questions the necessity of the inductive bias of locality in modern computer vision archi…
Revisiting Feature Prediction for Learning Visual Representations from Video
Adrien Bardes, Quentin Garrido, Jean Ponce +5
This paper explores feature prediction as a stand-alone objective for unsupervised learning from video and introduces V-JEPA, a collection of vision models trained solely using a f…