3 citations · 3 across the 5 of their papers we have counts for
5 papers
In Pursuit of Pixel Supervision for Visual Pre-training
Lihe Yang, Shang-Wen Li, Yang Li +5
At the most basic level, pixels are the source of the visual information through which we perceive the world. Pixels contain information at all levels, ranging from low-level attri…
Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search
Xin Lai, Junyi Li, Wei Li +3
Recent advances in large multimodal models have leveraged image-based tools with reinforcement learning to tackle visual problems. However, existing open-source approaches often ex…
BOOD: Boundary-based Out-Of-Distribution Data Generation
Qilin Liao, Shuo Yang, Bo Zhao +2
Harnessing the power of diffusion models to synthesize auxiliary training data based on latent space features has proven effective in enhancing out-of-distribution (OOD) detection…
PanDA: Towards Panoramic Depth Anything with Unlabeled Panoramas and Mobius Spatial Augmentation
Zidong Cao, Jinjing Zhu, Weiming Zhang +4
Recently, Depth Anything Models (DAMs) - a type of depth foundation models - have demonstrated impressive zero-shot capabilities across diverse perspective images. Despite its succ…
Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners
Zitian Chen, Yikang Shen, Mingyu Ding +4
Optimization in multi-task learning (MTL) is more challenging than single-task learning (STL), as the gradient from different tasks can be contradictory. When tasks are related, it…