10 papers
TIIF-Bench: How Does Your T2I Model Follow Your Instructions?
Xinyu Wei, Jinrui Zhang, Zeqing Wang +4
The rapid advancements of Text-to-Image (T2I) models have ushered in a new phase of AI-generated content, marked by their growing ability to interpret and follow user instructions.…
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…
Rethinking VLM Representation for VLA Initialization
Weifeng Lin, Siyuan Huang, Hao Li +5
Vision-Language-Action (VLA) models widely adopt pretrained Vision-Language Models (VLMs) as policy backbones, yet it remains unclear what kind of pretrained VLM representation is…
VideoVerse: Does Your T2V Generator Have World Model Capability to Synthesize Videos?
Zeqing Wang, Xinyu Wei, Bairui Li +5
The recent rapid advancement of Text-to-Video (T2V) generation technologies are engaging the trained models with more world model ability, making the existing benchmarks increasing…
MICo-150K: A Comprehensive Dataset Advancing Multi-Image Composition
Xinyu Wei, Kangrui Cen, Hongyang Wei +6
In controllable image generation, synthesizing coherent and consistent images from multiple reference inputs, i.e., Multi-Image Composition (MICo), remains a challenging problem, p…
GENIUS: Generative Fluid Intelligence Evaluation Suite
Ruichuan An, Sihan Yang, Ziyu Guo +8
Unified Multimodal Models (UMMs) have shown remarkable progress in visual generation. Yet, existing benchmarks predominantly assess , which reli…