294 citations · 3k across the 175 of their papers we have counts for
14 papers · 2 filters
Unified Coarse-to-Fine Alignment for Video-Text Retrieval
Ziyang Wang, Yi-Lin Sung, Feng Cheng +2
The canonical approach to video-text retrieval leverages a coarse-grained or fine-grained alignment between visual and textual information. However, retrieving the correct video ac…
VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planning
Han Lin, Abhay Zala, Jaemin Cho +1
Recent text-to-video (T2V) generation methods have seen significant advancements. However, the majority of these works focus on producing short video clips of a single event (i.e.,…
Scaling Data Generation in Vision-and-Language Navigation
Zun Wang, Jialu Li, Yicong Hong +6
Recent research in language-guided visual navigation has demonstrated a significant demand for the diversity of traversable environments and the quantity of supervision for trainin…
Adaptive Contextual Perception: How to Generalize to New Backgrounds and Ambiguous Objects
Zhuofan Ying, Peter Hase, Mohit Bansal
Biological vision systems make adaptive use of context to recognize objects in new settings with novel contexts as well as occluded or blurry objects in familiar settings. In this…
PanoGen: Text-Conditioned Panoramic Environment Generation for Vision-and-Language Navigation
Jialu Li, Mohit Bansal
Vision-and-Language Navigation (VLN) requires the agent to follow language instructions to navigate through 3D environments. One main challenge in VLN is the limited availability o…
Any-to-Any Generation via Composable Diffusion
Zineng Tang, Ziyi Yang, Chenguang Zhu +2
We present Composable Diffusion (CoDi), a novel generative model capable of generating any combination of output modalities, such as language, image, video, or audio, from any comb…