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cs.CV2026

DepthMaster: Unified Monocular Depth Estimation for Perspective and Panoramic Images

Pengfei Wang, Shihao Wang, Liyi Chen +3

While monocular depth estimation has achieved significant progress, achieving generalized metric depth estimation for both narrow field-of-view (FoV) perspectives and p…

cs.CV2026

LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding

Shihao Wang, Shilong Liu, Yuanguo Kuang +10

Vision-language models (VLMs) commonly formulate visual grounding and detection as a coordinate-token generation problem, serializing each 2D box into multiple 1D tokens that are l…

cs.CV2026

VOSR: A Vision-Only Generative Model for Image Super-Resolution

Rongyuan Wu, Lingchen Sun, Zhengqiang Zhang +4

Most of the recent generative image super-resolution (SR) methods rely on adapting large text-to-image (T2I) diffusion models pretrained on web-scale text-image data. While effecti…

cs.CV2025

PixelRefer: A Unified Framework for Spatio-Temporal Object Referring with Arbitrary Granularity

Yuqian Yuan, Wenqiao Zhang, Xin Li +6

Multimodal large language models (MLLMs) have demonstrated strong general-purpose capabilities in open-world visual comprehension. However, most existing MLLMs primarily focus on h…

cs.CV2025

DPO-SR: Direct Perceptual Preference Optimization for Real-World Image Super-Resolution

Rongyuan Wu, Lingchen Sun, Zhengqiang Zhang +5

Benefiting from pre-trained text-to-image (T2I) diffusion models, real-world image super-resolution (Real-ISR) methods can synthesize rich and realistic details. However, due to th…

cs.CV2025

VideoITG: Multimodal Video Understanding with Instructed Temporal Grounding

Shihao Wang, Guo Chen, De-an Huang +6

While Video Large Language Models (Video-LLMs) have shown significant potential in multimodal understanding and reasoning tasks, how to efficiently select the most informative fram…