collaborators

7 papers

cs.RO2026

Revision, Not Restart: Revisable Visual Plans for Closed-Loop World-Action Models

Pengyiang Liu, Junbo Niu, Wenhao Zheng +5

World-action models use predicted visual futures to condition robot actions, yet execution feedback can invalidate parts of a prediction while leaving its task structure useful. We…

cs.CV2026

When Should the Count Change? Learning State Maintenance for Causal Video Counting

Pengyiang Liu, Dongyue Lyu, Junbo Niu +3

Continuous video counting requires distinguishing new observations from new objects or completed events. We introduce StaMina (State Maintenance), which learns to maintain counting…

cs.CV2026

TRACE: Temporal Retrieval with Anchored and Convergent Evidence for Long-Horizon Video Understanding

Pengyiang Liu, Junbo Niu, Xiaoyang Hu +4

A long-video answer is evidence-supported only when the frames decoded from the video cover every event the answer depends on. Existing evaluations score final-answer correctness o…

cs.CV2026

OVO-S-Bench: A Hierarchical Benchmark for Streaming Spatial Intelligence in Multimodal LLMs

Yifei Li, Pengyiang Liu, Yuhang Zang +4

Multimodal agents in robotics, AR, and autonomous driving must reason about places and layouts from continuous egocentric streams, often using evidence outside the current view. Ex…

cs.CV2026

SVCBench: A Streaming Video Counting Benchmark for Spatial-Temporal State Maintenance

Pengyiang Liu, Zhongyue Shi, Hongye Hao +7

Video understanding requires models to continuously track and update world state during playback. Although existing benchmarks have advanced video understanding evaluation across m…

cs.CV2025

Dynamic-I2V: Exploring Image-to-Video Generation Models via Multimodal LLM

Peng Liu, Xiaoming Ren, Fengkai Liu +5

Recent advancements in image-to-video (I2V) generation have shown promising performance in conventional scenarios. However, these methods still encounter significant challenges whe…

cs.CV2025

H2VU-Benchmark: A Comprehensive Benchmark for Hierarchical Holistic Video Understanding

Qi Wu, Quanlong Zheng, Yanhao Zhang +8

With the rapid development of multimodal models, the demand for assessing video understanding capabilities has been steadily increasing. However, existing benchmarks for evaluating…