Aditya Murali
9 Papers
2 Citations
Aditya Murali is an academic researcher. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 2, co-authored 4 publications.
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Papers
CholecTriplet2022: Show me a tool and tell me the triplet - an endoscopic vision challenge for surgical action triplet detection
Saurav Sharma,Deepak Alapatt,Kun Yuan,Wolfgang Reiter,Amine Yamlahi,Guoyan Zheng,Helena R. Torres,Satoshi Kondo,Felix Holm,Shuangchun Gui,Sista Raviteja,Rachana Sathish,B N Bhattarai,Guo Rui,Melanie Schellenberg,Zhenkun Wang,Shrawan Kumar Thapa,Thuy Nuong Tran,Jaime C. Fonseca,Pietro Mascagni,Chinedu Innocent Nwoye,Tong Yu,Aditya Murali,Armine Vardazaryan,Jonas Hajek,Finn-Henri Smidt,Xiaoyang Zou,Bruno Oliveira,Satoshi Kasai,Ege Özsoy,Han Li,Pranav Poudel,Ziheng Wang,Joao L. Vilacca,Tobias Czempiel,Debdoot Sheet,Max Berniker,Patrick Godau,Pedro Morais,S. Regmi,Jan-Hinrich Nolke,Estevão Lima,Eduard Vazquez,Lena Maier-Hein,Nassir Navab,Barbara Seeliger,Cristians Gonzalez,Didier Mutter,Nicolas Padoy +48 more
TL;DR: The CholecTriplet2022 challenge as discussed by the authors extended surgical action triplet modeling from recognition to detection, which includes weakly-supervised bounding box localization of every visible surgical instrument (or tool), as the key actors, and modeling of each tool-activity in the form of triplet.
The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark
Aditya Murali,Deepak Alapatt,Pietro Mascagni,Armine Vardazaryan,Alain Garcia,Nariaki Okamoto,Guido Costamagna,Didier Mutter,Jacques Marescaux,Bernard Dallemagne,Nicolas Padoy +10 more
TL;DR: Detailed dataset statistics (size, class distribution, dataset splits, etc.) and a comprehensive performance benchmark for instance segmentation, object detection, and CVS prediction are provided.
CholecTriplet2022: Show me a tool and tell me the triplet - an endoscopic vision challenge for surgical action triplet detection
Chinedu Innocent Nwoye,Tong Yu,Saurav Sharma,Aditya Murali,Deepak Alapatt,Kun Yuan,Jonas Hajek,Wolfgang Reiter,Xiaoyang Zou,Bruno Oliveira,Helena R. Torres,Felix Holm,Ege Özsoy,Sista Raviteja,Rachana Sathish,Pranav Poudel,Guo Rui,Tobias Czempiel,Zhenkun Wang,Shrawan Kumar Thapa,Thuy Nuong Tran,Lena Maier-Hein,Nassir Navab,Cristians Gonzalez,Armine Vardazaryan,Amine Yamlahi,Finn-Henri Smidt,Guoyan Zheng,Satoshi Kondo,Satoshi Kasai,Shuangchun Gui,Han Li,B N Bhattarai,Ziheng Wang,Melanie Schellenberg,Joao L. Vilacca,Debdoot Sheet,Max Berniker,Patrick Godau,Pedro Morais,S. Regmi,Jaime C. Fonseca,Jan-Hinrich Nolke,Estevão Lima,Eduard Vazquez,Pietro Mascagni,Barbara Seeliger,Didier Mutter,Nicolas Padoy +48 more
TL;DR: The CholecTriplet2022 challenge as mentioned in this paper extended surgical action triplet modeling from recognition to detection, which includes weakly-supervised bounding box localization of every visible surgical instrument (or tool), as the key actors, and modeling of each tool-activity in the form of triplet.
4
Optimizing latent graph representations of surgical scenes for unseen domain generalization.
Siddhant Satyanaik,Aditya Murali,Deepak Alapatt,Pietro Mascagni,Nicolas Padoy +4 more
TL;DR: It is shown that object-centric approaches are highly effective for domain generalization thanks to their modular approach to representation learning, and an optimized approach is developed that substantially outperforms existing methods.
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Optimizing Latent Graph Representations of Surgical Scenes for Zero-Shot Domain Transfer
Siddhant Satyanaik,Aditya Murali,Deepak Alapatt,Xin Wang,Pietro Mascagni,Nicolas Padoy +5 more
TL;DR: Optimizing latent graph representations of surgical scenes for zero-shot domain transfer achieves significant domain generalization improvements by leveraging the disentangled nature of object-centric representations.
1