publications

2026

1. ACMMM

   EMODY Flow: Emotion-Aware Audio-Driven Full-Body Motion Generation

   Harsh Kumar Agarwal, Xavier Alameda-Pineda, and Olivier Perrotin

   In Proceedings of the 1st International Workshop on Joint Audio-Video Comprehension and Generation (JAV-CG), co-located with ACM Multimedia, 2026

   Accepted

   Abs Bib HTML

   Embodied conversational agents require synchronized full-body motion (body gestures and facial expressions) that aligns with speech and emotional state. We identify and address a failure of emotion conditioning: a flow-matching model given both a rich audio embedding and a discrete emotion label suppresses the emotion, generating near-identical motion regardless of the specified emotion. We present EMODY Flow, a lightweight ( 35M parameter) flow-matching framework that attaches to a frozen Qwen-3 Omni model and reuses its internal Mimi audio-codecs to condition two parallel DiT generators – one for SMPL-X body pose, one for FLAME facial expressions. A training-time auxiliary emotion classifier restores emotion sensitivity by forcing generated motion to be emotion-identifiable. EMODY Flow sets a new state of the art on BEAT2 gesture quality, with FGD 0.302, Beat Correlation 0.853, and Diversity 24.62 – improving over the best prior results by 26%, 5%, and 62% respectively – and transfers to zero-shot facial animation on TFHP without domain-specific fine-tuning.

   @inproceedings{agarwal2026emody,
     title = {{EMODY} Flow: Emotion-Aware Audio-Driven Full-Body Motion Generation},
     author = {Agarwal, Harsh Kumar and Alameda-Pineda, Xavier and Perrotin, Olivier},
     booktitle = {Proceedings of the 1st International Workshop on Joint Audio-Video Comprehension and Generation (JAV-CG), co-located with ACM Multimedia},
     year = {2026},
     archiveprefix = {arXiv},
     note = {Accepted}
   }

2025

1. ICDMW

   Cross-Cultural Recipe Transformation Via Neural Network and Encoder-Based Models

   Vibhuti Dhar Khanduri, Mansi Goel, Lakshay Dabas, and 1 more author

   In 2025 IEEE International Conference on Data Mining Workshops (ICDMW), 2025

   Abs Bib

   Developed a neural network classifier to identify cuisine types from recipes. Created an unsupervised ingredient substitution method via semantic embeddings, achieving 90% accuracy in cuisine preservation after cross-cultural transformation.

   @inproceedings{khanduri2025cross,
     title = {Cross-Cultural Recipe Transformation Via Neural Network and Encoder-Based Models},
     author = {Khanduri, Vibhuti Dhar and Goel, Mansi and Dabas, Lakshay and Agarwal, Harsh Kumar},
     booktitle = {2025 IEEE International Conference on Data Mining Workshops (ICDMW)},
     pages = {633--640},
     year = {2025},
     organization = {IEEE},
   }

2024

1. WACV

   SICKLE: A Multi-Sensor Satellite Imagery Dataset Annotated With Multiple Key Cropping Parameters

   Depanshu Sani, Sandeep Mahato, Sourabh Saini, and 5 more authors

   In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024

   Oral Presentation

   Abs Bib HTML

   Multi-spectral satellite dataset for key cropping parameters annotated at multiple spatial resolutions (3m, 10m, and 30m). Enables benchmarking of ML models for precision agriculture applications including crop type mapping and yield prediction.

   @inproceedings{sani2024sickle,
     title = {{SICKLE}: A Multi-Sensor Satellite Imagery Dataset Annotated With Multiple Key Cropping Parameters},
     author = {Sani, Depanshu and Mahato, Sandeep and Saini, Sourabh and Agarwal, Harsh Kumar and Devshali, Charu Chandra and Anand, Saket and Arora, Gaurav and Jayaraman, Thiagarajan},
     booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
     pages = {5995--6004},
     year = {2024},
     note = {Oral Presentation}
   }