3 citations · 4 across the 6 of their papers we have counts for
6 papers
NEST: Narrative Event Structures in Time for Long Video Understanding
Ali Asgarov, Kaushik Narasimhan, Najibul Haque Sarker +6
Recent progress in vision-language models has enabled processing of increasingly long video sequences, but handling extended token streams does not translate to understanding compl…
Enhanced Chart Understanding in Vision and Language Task via Cross-modal Pre-training on Plot Table Pairs
Mingyang Zhou, Yi R. Fung, Long Chen +3
Building cross-model intelligence that can understand charts and communicate the salient information hidden behind them is an appealing challenge in the vision and language(V+L) co…
Weakly-Supervised Temporal Article Grounding
Long Chen, Yulei Niu, Brian Chen +6
Given a long untrimmed video and natural language queries, video grounding (VG) aims to temporally localize the semantically-aligned video segments. Almost all existing VG work hol…
Beyond Grounding: Extracting Fine-Grained Event Hierarchies Across Modalities
Hammad A. Ayyubi, Christopher Thomas, Lovish Chum +8
Events describe happenings in our world that are of importance. Naturally, understanding events mentioned in multimedia content and how they are related forms an important way of c…
Fine-Grained Visual Entailment
Christopher Thomas, Yipeng Zhang, Shih-Fu Chang
Visual entailment is a recently proposed multimodal reasoning task where the goal is to predict the logical relationship of a piece of text to an image. In this paper, we propose a…
Joint Multimedia Event Extraction from Video and Article
Brian Chen, Xudong Lin, Christopher Thomas +5
Visual and textual modalities contribute complementary information about events described in multimedia documents. Videos contain rich dynamics and detailed unfoldings of events, w…