1 citations · 1 across the 12 of their papers we have counts for
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Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning
Zuyao You, Zuxuan Wu
We present Seg-R1, a preliminary exploration of using reinforcement learning (RL) to enhance the pixel-level understanding and reasoning capabilities of large multimodal models (LM…
Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation
Kailin Li, Zhenxin Li, Shiyi Lan +6
Hydra-MDP++ introduces a novel teacher-student knowledge distillation framework with a multi-head decoder that learns from human demonstrations and rule-based experts. Using a ligh…
Pix2Cap-COCO: Advancing Visual Comprehension via Pixel-Level Captioning
Zuyao You, Junke Wang, Lingyu Kong +2
We present Pix2Cap-COCO, the first panoptic pixel-level caption dataset designed to advance fine-grained visual understanding. To achieve this, we carefully design an automated ann…
FOCUS: Towards Universal Foreground Segmentation
Zuyao You, Lingyu Kong, Lingchen Meng +1
Foreground segmentation is a fundamental task in computer vision, encompassing various subdivision tasks. Previous research has typically designed task-specific architectures for e…
BEVNeXt: Reviving Dense BEV Frameworks for 3D Object Detection
Zhenxin Li, Shiyi Lan, Jose M. Alvarez +1
Recently, the rise of query-based Transformer decoders is reshaping camera-based 3D object detection. These query-based decoders are surpassing the traditional dense BEV (Bird's Ey…
Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vision-Language Understanding
Wujian Peng, Sicheng Xie, Zuyao You +2
Vision language models (VLM) have demonstrated remarkable performance across various downstream tasks. However, understanding fine-grained visual-linguistic concepts, such as attri…