5 papers · 1 filter
BVB: Benchmarking Agentic Video Understanding via Programmatic Reconstruction in Blender
Yolo Y. Tang, Daiki Shimada, Jiayue Meng +14
Multimodal agents can create complex videos in software such as Blender by writing code instead of using diffusion models. Yet video understanding benchmarks still evaluate models…
Suppression Is Not Forgetting: Residual Recoverability in Visual Concept Unlearning for VLMs
Zhangyun Tan, Zeliang Zhang, Jiani Liu +5
Vision-language models (VLMs) may need to forget visual concepts after deployment because of privacy, copyright, licensing, safety, or policy changes. Conventional machine unlearni…
TDMM-LM: Bridging Facial Understanding and Animation via Language Models
Luchuan Song, Pinxin Liu, Haiyang Liu +7
Text-guided human body animation has advanced rapidly, yet facial animation lags due to the scarcity of well-annotated, text-paired facial corpora. To close this gap, we leverage f…
Omni-Judge: Can Omni-LLMs Serve as Human-Aligned Judges for Text-Conditioned Audio-Video Generation?
Susan Liang, Chao Huang, Filippos Bellos +7
State-of-the-art text-to-video generation models such as Sora 2 and Veo 3 can now produce high-fidelity videos with synchronized audio directly from a textual prompt, marking a new…
Video-R4: Reinforcing Text-Rich Video Reasoning with Visual Rumination
Yolo Y. Tang, Daiki Shimada, Hang Hua +4
Understanding text-rich videos requires reading small, transient textual cues that often demand repeated inspection. Yet most video QA models rely on single-pass perception over fi…