6 papers
Where, How, and When: Query-Guided Grounding for Video Understanding
Yogesh Kumar
Understanding video content requires reasoning at multiple levels of granularity, from identifying objects to interpreting their interactions and localizing when specific actions o…
Strictly Causal Streaming Video Anomaly Detection with a Theoretically-Grounded State-Space Core
Yogesh Kumar
Recent work has applied Mamba style state space models (SSMs) to video anomaly detection, yet existing approaches still rely on buffering clips or windows internally, lack a theore…
Catching Hallucinated Citations in Video-LLM Question Answering: A Self-Verification Pipeline and Verifier Ablation Study
Yogesh Kumar
Video question answering systems built on vision-language models often produce timestamped claims with high confidence even when unsupported by the cited frame. This deceptive hall…
Temporal Object-Aware Vision Transformer for Few-Shot Video Object Detection
Yogesh Kumar, Anand Mishra
Few-shot Video Object Detection (FSVOD) addresses the challenge of detecting novel objects in videos with limited labeled examples, overcoming the constraints of traditional detect…
Aligning Moments in Time using Video Queries
Yogesh Kumar, Uday Agarwal, Manish Gupta +1
Video-to-video moment retrieval (Vid2VidMR) is the task of localizing unseen events or moments in a target video using a query video. This task poses several challenges, such as th…
Towards Making Flowchart Images Machine Interpretable
Shreya Shukla, Prajwal Gatti, Yogesh Kumar +2
Computer programming textbooks and software documentations often contain flowcharts to illustrate the flow of an algorithm or procedure. Modern OCR engines often tag these flowchar…