activity
20242026
collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2026

SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning

Seokju Cho, Ryo Hachiuma, Abhishek Badki +8

Spatial reasoning, the ability to determine where objects are, how they relate, and how they move in 3D, remains a fundamental challenge for vision-language models (VLMs). Tool-aug…

cs.CV2025

4D-RGPT: Toward Region-level 4D Understanding via Perceptual Distillation

Chiao-An Yang, Ryo Hachiuma, Sifei Liu +4

Despite advances in Multimodal LLMs (MLLMs), their ability to reason over 3D structures and temporal dynamics remains limited, constrained by weak 4D perception and temporal unders…

cs.CV2025

Temporal Prompting Matters: Rethinking Referring Video Object Segmentation

Ci-Siang Lin, Min-Hung Chen, I-Jieh Liu +3

Referring Video Object Segmentation (RVOS) aims to segment the object referred to by the query sentence in the video. Most existing methods require end-to-end training with dense m…

cs.CV2025

Describe Anything: Detailed Localized Image and Video Captioning

Long Lian, Yifan Ding, Yunhao Ge +8

Generating detailed and accurate descriptions for specific regions in images and videos remains a fundamental challenge for vision-language models. We introduce the Describe Anythi…

cs.CV2025

Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks

Miran Heo, Min-Hung Chen, De-An Huang +5

We present Omni-RGPT, a multimodal large language model designed to facilitate region-level comprehension for both images and videos. To achieve consistent region representation ac…

cs.CV2024

SSE: Multimodal Semantic Data Selection and Enrichment for Industrial-scale Data Assimilation

Maying Shen, Nadine Chang, Sifei Liu +1

In recent years, the data collected for artificial intelligence has grown to an unmanageable amount. Particularly within industrial applications, such as autonomous vehicles, model…

cs.CV2024

GroPrompt: Efficient Grounded Prompting and Adaptation for Referring Video Object Segmentation

Ci-Siang Lin, I-Jieh Liu, Min-Hung Chen +3

Referring Video Object Segmentation (RVOS) aims to segment the object referred to by the query sentence throughout the entire video. Most existing methods require end-to-end traini…