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2020 – today
- 2024
[c53]Madeline Chantry Schiappa, Shehreen Azad, Sachidanand VS, Yunhao Ge, Ondrej Miksik, Yogesh S. Rawat, Vibhav Vineet:
Robustness Analysis on Foundational Segmentation Models. CVPR Workshops 2024: 1786-1796- [c52]Yash Jain, Anshul Nasery, Vibhav Vineet, Harkirat S. Behl:
Peekaboo: Interactive Video Generation via Masked-Diffusion. CVPR 2024: 8079-8088 - [i47]Shresth Grover, Vibhav Vineet, Yogesh S. Rawat:
Navigating Hallucinations for Reasoning of Unintentional Activities. CoRR abs/2402.19405 (2024) - [i46]Joykirat Singh, Akshay Nambi, Vibhav Vineet:
Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning. CoRR abs/2406.10834 (2024) - [i45]Jiayu Wang, Yifei Ming, Zhenmei Shi, Vibhav Vineet, Xin Wang, Neel Joshi:
Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models. CoRR abs/2406.14852 (2024) - [i44]Shehreen Azad, Yash Jain, Rishit Garg, Yogesh S. Rawat, Vibhav Vineet:
GeoMeter: Probing Depth and Height Perception of Large Visual-Language Models. CoRR abs/2408.11748 (2024) - [i43]Vidhisha Balachandran, Jingya Chen, Neel Joshi, Besmira Nushi, Hamid Palangi, Eduardo Salinas, Vibhav Vineet, James Woffinden-Luey, Safoora Yousefi:
Eureka: Evaluating and Understanding Large Foundation Models. CoRR abs/2409.10566 (2024) - 2023
- [c51]Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov:
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRL 2023: 2624-2641 - [c50]Madeline Chantry Schiappa, Naman Biyani, Prudvi Kamtam, Shruti Vyas, Hamid Palangi, Vibhav Vineet, Yogesh S. Rawat:
A Large-Scale Robustness Analysis of Video Action Recognition Models. CVPR 2023: 14698-14708 - [c49]Nishant Jain, Harkirat S. Behl, Yogesh Singh Rawat, Vibhav Vineet:
Efficiently Robustify Pre-Trained Models. ICCV 2023: 5482-5492 - [c48]Sruthi Sudhakar, Jon Hanzelka, Josh Bobillot, Tanmay Randhavane, Neel Joshi, Vibhav Vineet:
Exploring the Sim2Real Gap using Digital Twins. ICCV 2023: 20361-20370 - [c47]Shresth Grover, Vibhav Vineet, Yogesh S. Rawat:
Revealing the unseen: Benchmarking video action recognition under occlusion. NeurIPS 2023 - [c46]Yash Jain, Harkirat S. Behl, Zsolt Kira, Vibhav Vineet:
DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets. NeurIPS 2023 - [c45]Rajat Modi, Vibhav Vineet, Yogesh S. Rawat:
On Occlusions in Video Action Detection: Benchmark Datasets And Training Recipes. NeurIPS 2023 - [c44]Tyler LaBonte, Yale Song, Xin Wang, Vibhav Vineet, Neel Joshi:
Scaling Novel Object Detection with Weakly Supervised Detection Transformers. WACV 2023: 85-96 - [i42]Garrett Thomas, Ching-An Cheng, Ricky Loynd, Vibhav Vineet, Mihai Jalobeanu, Andrey Kolobov:
PLEX: Making the Most of the Available Data for Robotic Manipulation Pretraining. CoRR abs/2303.08789 (2023) - [i41]Tianjun Zhang, Yi Zhang, Vibhav Vineet, Neel Joshi, Xin Wang:
Controllable Text-to-Image Generation with GPT-4. CoRR abs/2305.18583 (2023) - [i40]Akash Kumar, Ashlesha Kumar, Vibhav Vineet, Yogesh Singh Rawat:
Benchmarking self-supervised video representation learning. CoRR abs/2306.06010 (2023) - [i39]Madeline Chantry Schiappa, Sachidanand VS, Yunhao Ge, Ondrej Miksik, Yogesh S. Rawat, Vibhav Vineet:
Robustness Analysis on Foundational Segmentation Models. CoRR abs/2306.09278 (2023) - [i38]Yunhao Ge, Jiashu Xu, Brian Nlong Zhao, Neel Joshi, Laurent Itti, Vibhav Vineet:
Beyond Generation: Harnessing Text to Image Models for Object Detection and Segmentation. CoRR abs/2309.05956 (2023) - [i37]Nishant Jain, Harkirat S. Behl, Yogesh Singh Rawat, Vibhav Vineet:
Efficiently Robustify Pre-trained Models. CoRR abs/2309.07499 (2023) - [i36]Yash Jain, Harkirat S. Behl, Zsolt Kira, Vibhav Vineet:
DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets. CoRR abs/2311.04894 (2023) - [i35]Yash Jain, Anshul Nasery, Vibhav Vineet, Harkirat S. Behl:
PEEKABOO: Interactive Video Generation via Masked-Diffusion. CoRR abs/2312.07509 (2023) - [i34]Brian Nlong Zhao, Yuhang Xiao
, Jiashu Xu, Xinyang Jiang, Yifan Yang, Dongsheng Li, Laurent Itti, Vibhav Vineet, Yunhao Ge:
DreamDistribution: Prompt Distribution Learning for Text-to-Image Diffusion Models. CoRR abs/2312.14216 (2023) - 2022
- [c43]Benno Krojer, Vaibhav Adlakha, Vibhav Vineet, Yash Goyal, Edoardo Maria Ponti, Siva Reddy:
Image Retrieval from Contextual Descriptions. ACL (1) 2022: 3426-3440 - [c42]Daniel McDuff, Yale Song, Jiyoung Lee, Vibhav Vineet, Sai Vemprala, Nicholas Gyde, Hadi Salman, Shuang Ma, Kwanghoon Sohn, Ashish Kapoor:
CausalCity: Complex Simulations with Agency for Causal Discovery and Reasoning. CLeaR 2022: 559-575 - [c41]Weizhe Liu, Bugra Tekin, Huseyin Coskun, Vibhav Vineet, Pascal Fua, Marc Pollefeys:
Learning to Align Sequential Actions in the Wild. CVPR 2022: 2171-2181 - [c40]Ching-Yao Chuang, R. Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song:
Robust Contrastive Learning against Noisy Views. CVPR 2022: 16649-16660 - [c39]Xiaogang Xu, Hengshuang Zhao, Vibhav Vineet, Ser-Nam Lim, Antonio Torralba:
MTFormer: Multi-task Learning via Transformer and Cross-Task Reasoning. ECCV (27) 2022: 304-321 - [c38]Yunhao Ge, Harkirat S. Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet:
Neural-Sim: Learning to Generate Training Data with NeRF. ECCV (23) 2022: 477-493 - [c37]Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry:
Missingness Bias in Model Debugging. ICLR 2022 - [c36]Benoît Guillard, Sai Vemprala, Jayesh K. Gupta, Ondrej Miksik, Vibhav Vineet, Pascal Fua, Ashish Kapoor:
Learning to Simulate Realistic LiDARs. IROS 2022: 8173-8180 - [c35]Eric Heiden, Ziang Liu, Vibhav Vineet, Erwin Coumans, Gaurav S. Sukhatme:
Inferring Articulated Rigid Body Dynamics from RGBD Video. IROS 2022: 8383-8390 - [c34]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. NeurIPS 2022 - [c33]Madeline Schiappa, Shruti Vyas, Hamid Palangi, Yogesh S. Rawat, Vibhav Vineet:
Robustness Analysis of Video-Language Models Against Visual and Language Perturbations. NeurIPS 2022 - [i33]Ching-Yao Chuang, R. Devon Hjelm, Xin Wang, Vibhav Vineet, Neel Joshi, Antonio Torralba, Stefanie Jegelka, Yale Song:
Robust Contrastive Learning against Noisy Views. CoRR abs/2201.04309 (2022) - [i32]Sharath Girish, Debadeepta Dey, Neel Joshi, Vibhav Vineet, Shital Shah, Caio César Teodoro Mendes, Abhinav Shrivastava, Yale Song:
One Network Doesn't Rule Them All: Moving Beyond Handcrafted Architectures in Self-Supervised Learning. CoRR abs/2203.08130 (2022) - [i31]Eric Heiden, Ziang Liu, Vibhav Vineet, Erwin Coumans, Gaurav S. Sukhatme:
Inferring Articulated Rigid Body Dynamics from RGBD Video. CoRR abs/2203.10488 (2022) - [i30]Benno Krojer, Vaibhav Adlakha, Vibhav Vineet, Yash Goyal, Edoardo Maria Ponti, Siva Reddy:
Image Retrieval from Contextual Descriptions. CoRR abs/2203.15867 (2022) - [i29]Saachi Jain, Hadi Salman, Eric Wong, Pengchuan Zhang, Vibhav Vineet, Sai Vemprala, Aleksander Madry:
Missingness Bias in Model Debugging. CoRR abs/2204.08945 (2022) - [i28]Yunhao Ge, Jiashu Xu, Brian Nlong Zhao, Laurent Itti, Vibhav Vineet:
DALL-E for Detection: Language-driven Context Image Synthesis for Object Detection. CoRR abs/2206.09592 (2022) - [i27]Madeline C. Schiappa, Naman Biyani, Shruti Vyas, Hamid Palangi, Vibhav Vineet, Yogesh S. Rawat:
Large-scale Robustness Analysis of Video Action Recognition Models. CoRR abs/2207.01398 (2022) - [i26]Madeline C. Schiappa, Shruti Vyas, Hamid Palangi, Yogesh S. Rawat, Vibhav Vineet:
Multi-modal Robustness Analysis Against Language and Visual Perturbations. CoRR abs/2207.02159 (2022) - [i25]Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti:
TASKOGRAPHY: Evaluating robot task planning over large 3D scene graphs. CoRR abs/2207.05006 (2022) - [i24]Tyler LaBonte, Yale Song, Xin Wang, Vibhav Vineet, Neel Joshi:
Scaling Novel Object Detection with Weakly Supervised Detection Transformers. CoRR abs/2207.05205 (2022) - [i23]Yunhao Ge, Harkirat S. Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet:
Neural-Sim: Learning to Generate Training Data with NeRF. CoRR abs/2207.11368 (2022) - [i22]Benoît Guillard, Sai Vemprala, Jayesh K. Gupta, Ondrej Miksik, Vibhav Vineet, Pascal Fua, Ashish Kapoor:
Learning to Simulate Realistic LiDARs. CoRR abs/2209.10986 (2022) - [i21]Jinoh Cho, Minguk Kang, Vibhav Vineet, Jaesik Park:
Context-Aware Image Completion. CoRR abs/2210.12350 (2022) - [i20]Yunhao Ge, Jiashu Xu, Brian Nlong Zhao, Laurent Itti, Vibhav Vineet:
EM-Paste: EM-guided Cut-Paste with DALL-E Augmentation for Image-level Weakly Supervised Instance Segmentation. CoRR abs/2212.07629 (2022) - [i19]Tejas Gokhale, Hamid Palangi, Besmira Nushi, Vibhav Vineet, Eric Horvitz, Ece Kamar, Chitta Baral, Yezhou Yang:
Benchmarking Spatial Relationships in Text-to-Image Generation. CoRR abs/2212.10015 (2022) - 2021
- [c32]Christopher Agia, Krishna Murthy Jatavallabhula, Mohamed Khodeir, Ondrej Miksik, Vibhav Vineet, Mustafa Mukadam, Liam Paull, Florian Shkurti:
Taskography: Evaluating robot task planning over large 3D scene graphs. CoRL 2021: 46-58 - [c31]Ziqi Fan, Vibhav Vineet, Chenshen Lu, T. W. Wu, Kyla A. McMullen:
Prediction of Object Geometry from Acoustic Scattering Using Convolutional Neural Networks. ICASSP 2021: 471-475 - [i18]Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard I. Hartley:
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs. CoRR abs/2103.08457 (2021) - [i17]Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry:
3DB: A Framework for Debugging Computer Vision Models. CoRR abs/2106.03805 (2021) - [i16]Daniel McDuff, Yale Song, Jiyoung Lee, Vibhav Vineet, Sai Vemprala, Nicholas Gyde, Hadi Salman, Shuang Ma, Kwanghoon Sohn, Ashish Kapoor:
CausalCity: Complex Simulations with Agency for Causal Discovery and Reasoning. CoRR abs/2106.13364 (2021) - [i15]Weizhe Liu, Bugra Tekin, Huseyin Coskun, Vibhav Vineet, Pascal Fua, Marc Pollefeys:
Learning to Align Sequential Actions in the Wild. CoRR abs/2111.09301 (2021) - 2020
- [c30]Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard I. Hartley:
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs. 3DV 2020: 180-189 - [c29]Pallabi Ghosh, Vibhav Vineet, Larry S. Davis, Abhinav Shrivastava, Sudipta N. Sinha, Neel Joshi:
Depth Completion Using a View-constrained Deep Prior. 3DV 2020: 723-733 - [c28]Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet:
AutoSimulate: (Quickly) Learning Synthetic Data Generation. ECCV (22) 2020: 255-271 - [c27]Ziqi Fan, Vibhav Vineet, Hannes Gamper, Nikunj Raghuvanshi:
Fast Acoustic Scattering Using Convolutional Neural Networks. ICASSP 2020: 171-175 - [c26]Rogerio Bonatti, Ratnesh Madaan, Vibhav Vineet, Sebastian A. Scherer, Ashish Kapoor:
Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations. IROS 2020: 1637-1644 - [i14]Pallabi Ghosh, Vibhav Vineet, Larry S. Davis, Abhinav Shrivastava, Sudipta N. Sinha, Neel Joshi:
Deep Depth Prior for Multi-View Stereo. CoRR abs/2001.07791 (2020) - [i13]Harkirat Singh Behl, Atilim Günes Baydin, Ran Gal, Philip H. S. Torr, Vibhav Vineet:
AutoSimulate: (Quickly) Learning Synthetic Data Generation. CoRR abs/2008.08424 (2020) - [i12]Zhiwei Xu, Thalaiyasingam Ajanthan, Vibhav Vineet, Richard I. Hartley:
RANP: Resource Aware Neuron Pruning at Initialization for 3D CNNs. CoRR abs/2010.02488 (2020) - [i11]Ziqi Fan, Vibhav Vineet, Chenshen Lu, Kyla A. McMullen:
Prediction of Object Geometry from Acoustic Scattering Using Convolutional Neural Networks. CoRR abs/2010.10691 (2020)
2010 – 2019
- 2019
- [c25]Zihao W. Wang, Vibhav Vineet, Francesco Pittaluga, Sudipta N. Sinha, Oliver Cossairt, Sing Bing Kang:
Privacy-Preserving Action Recognition Using Coded Aperture Videos. CVPR Workshops 2019: 1-10 - [c24]Ondrej Miksik, Vibhav Vineet:
Live Reconstruction of Large-Scale Dynamic Outdoor Worlds. CVPR Workshops 2019: 9-18 - [c23]Tomás Hodan, Vibhav Vineet, Ran Gal, Emanuel Shalev, Jon Hanzelka, Treb Connell, Pedro Urbina, Sudipta N. Sinha, Brian Guenter:
Photorealistic Image Synthesis for Object Instance Detection. ICIP 2019: 66-70 - [i10]Tomas Hodan, Vibhav Vineet, Ran Gal, Emanuel Shalev, Jon Hanzelka, Treb Connell, Pedro Urbina, Sudipta N. Sinha, Brian Guenter:
Photorealistic Image Synthesis for Object Instance Detection. CoRR abs/1902.03334 (2019) - [i9]Zihao W. Wang, Vibhav Vineet, Francesco Pittaluga, Sudipta N. Sinha, Oliver Cossairt, Sing Bing Kang:
Privacy-Preserving Action Recognition using Coded Aperture Videos. CoRR abs/1902.09085 (2019) - [i8]Ondrej Miksik, Vibhav Vineet:
Live Reconstruction of Large-Scale Dynamic Outdoor Worlds. CoRR abs/1903.06708 (2019) - [i7]Rogerio Bonatti, Ratnesh Madaan, Vibhav Vineet, Sebastian A. Scherer, Ashish Kapoor:
Learning Controls Using Cross-Modal Representations: Bridging Simulation and Reality for Drone Racing. CoRR abs/1909.06993 (2019) - [i6]Ziqi Fan, Vibhav Vineet, Hannes Gamper, Nikunj Raghuvanshi:
Fast acoustic scattering using convolutional neural networks. CoRR abs/1911.01802 (2019) - 2016
- [j4]Sam Hare, Stuart Golodetz, Amir Saffari, Vibhav Vineet, Ming-Ming Cheng, Stephen L. Hicks, Philip H. S. Torr:
Struck: Structured Output Tracking with Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 38(10): 2096-2109 (2016) - [c22]Abhijit Kundu, Vibhav Vineet, Vladlen Koltun:
Feature Space Optimization for Semantic Video Segmentation. CVPR 2016: 3168-3175 - [c21]René Ranftl, Vibhav Vineet, Qifeng Chen, Vladlen Koltun:
Dense Monocular Depth Estimation in Complex Dynamic Scenes. CVPR 2016: 4058-4066 - [c20]Stephan R. Richter, Vibhav Vineet, Stefan Roth, Vladlen Koltun:
Playing for Data: Ground Truth from Computer Games. ECCV (2) 2016: 102-118 - [i5]Stephan R. Richter, Vibhav Vineet, Stefan Roth, Vladlen Koltun:
Playing for Data: Ground Truth from Computer Games. CoRR abs/1608.02192 (2016) - 2015
- [j3]Julien P. C. Valentin, Vibhav Vineet, Ming-Ming Cheng, David Kim, Jamie Shotton, Pushmeet Kohli, Matthias Nießner, Antonio Criminisi, Shahram Izadi, Philip H. S. Torr:
SemanticPaint: Interactive 3D Labeling and Learning at your Fingertips. ACM Trans. Graph. 34(5): 154:1-154:17 (2015) - [c19]Ondrej Miksik, Vibhav Vineet, Morten Lidegaard, Ram Prasaath, Matthias Nießner, Stuart Golodetz, Stephen L. Hicks, Patrick Pérez, Shahram Izadi, Philip H. S. Torr:
The Semantic Paintbrush: Interactive 3D Mapping and Recognition in Large Outdoor Spaces. CHI 2015: 3317-3326 - [c18]Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr:
Conditional Random Fields as Recurrent Neural Networks. ICCV 2015: 1529-1537 - [c17]Vibhav Vineet, Ondrej Miksik, Morten Lidegaard, Matthias Nießner, Stuart Golodetz, Victor Adrian Prisacariu, Olaf Kähler, David William Murray, Shahram Izadi, Patrick Pérez, Philip H. S. Torr:
Incremental dense semantic stereo fusion for large-scale semantic scene reconstruction. ICRA 2015: 75-82 - [c16]Ondrej Miksik, Yousef Amar, Vibhav Vineet, Patrick Pérez, Philip H. S. Torr:
Incremental dense multi-modal 3D scene reconstruction. IROS 2015: 908-915 - [c15]Stuart Golodetz, Michael Sapienza, Julien P. C. Valentin, Vibhav Vineet, Ming-Ming Cheng, Victor Adrian Prisacariu, Olaf Kähler, Carl Yuheng Ren, Anurag Arnab, Stephen L. Hicks, David William Murray, Shahram Izadi, Philip H. S. Torr:
SemanticPaint: interactive segmentation and learning of 3D worlds. SIGGRAPH Emerging Technologies 2015: 22:1 - [c14]Julien P. C. Valentin, Vibhav Vineet, Ming-Ming Cheng, David Kim, Jamie Shotton, Pushmeet Kohli, Matthias Nießner, Antonio Criminisi, Shahram Izadi, Philip H. S. Torr:
SemanticPaint: interactive segmentation and learning of 3D world. SIGGRAPH Talks 2015: 75:1 - [i4]Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr:
Conditional Random Fields as Recurrent Neural Networks. CoRR abs/1502.03240 (2015) - [i3]Stuart Golodetz, Michael Sapienza, Julien P. C. Valentin, Vibhav Vineet, Ming-Ming Cheng, Anurag Arnab, Victor Adrian Prisacariu, Olaf Kähler, Carl Yuheng Ren, David William Murray, Shahram Izadi, Philip H. S. Torr:
SemanticPaint: A Framework for the Interactive Segmentation of 3D Scenes. CoRR abs/1510.03727 (2015) - 2014
- [b1]Vibhav Vineet:
Recognition, reorganisation, reconstruction and reinteraction for scene understanding. Oxford Brookes University, UK, 2014 - [j2]Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr:
Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces. Int. J. Comput. Vis. 110(3): 290-307 (2014) - [j1]Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin, Vibhav Vineet, Paul Sturgess, Nigel T. Crook, Niloy J. Mitra, Philip H. S. Torr:
ImageSpirit: Verbal Guided Image Parsing. ACM Trans. Graph. 34(1): 3:1-3:11 (2014) - [c13]Ondrej Miksik, Vibhav Vineet, Patrick Pérez, Philip H. S. Torr:
Distributed Non-convex ADMM-based inference in large-scale random fields. BMVC 2014 - [c12]Shuai Zheng, Ming-Ming Cheng, Jonathan Warrell, Paul Sturgess, Vibhav Vineet, Carsten Rother, Philip H. S. Torr:
Dense Semantic Image Segmentation with Objects and Attributes. CVPR 2014: 3214-3221 - [c11]Matej Kristan, Roman P. Pflugfelder, Ales Leonardis, Jiri Matas, Luka Cehovin, Georg Nebehay, Tomás Vojír, Gustavo Fernández, Alan Lukezic, Aleksandar Dimitriev, Alfredo Petrosino, Amir Saffari, Bo Li, Bohyung Han, Cherkeng Heng, Christophe Garcia, Dominik Pangersic, Gustav Häger, Fahad Shahbaz Khan, Franci Oven, Horst Possegger, Horst Bischof, Hyeonseob Nam, Jianke Zhu, Jijia Li, Jin Young Choi, Jinwoo Choi, João F. Henriques, Joost van de Weijer, Jorge Batista, Karel Lebeda, Kristoffer Öfjäll, Kwang Moo Yi, Lei Qin, Longyin Wen, Mario Edoardo Maresca, Martin Danelljan, Michael Felsberg, Ming-Ming Cheng, Philip H. S. Torr, Qingming Huang, Richard Bowden, Sam Hare, Samantha YueYing Lim, Seunghoon Hong, Shengcai Liao, Simon Hadfield, Stan Z. Li, Stefan Duffner, Stuart Golodetz, Thomas Mauthner, Vibhav Vineet, Weiyao Lin, Yang Li, Yuankai Qi, Zhen Lei, Zhi Heng Niu:
The Visual Object Tracking VOT2014 Challenge Results. ECCV Workshops (2) 2014: 191-217 - [i2]Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr:
A Tiered Move-making Algorithm for General Non-submodular Pairwise Energies. CoRR abs/1403.6275 (2014) - 2013
- [c10]Vibhav Vineet, Glenn Sheasby, Jonathan Warrell, Philip H. S. Torr:
PoseField: An Efficient Mean-Field Based Method for Joint Estimation of Human Pose, Segmentation, and Depth. EMMCVPR 2013: 180-194 - [c9]Ming-Ming Cheng, Jonathan Warrell, Wen-Yan Lin, Shuai Zheng, Vibhav Vineet, Nigel T. Crook:
Efficient Salient Region Detection with Soft Image Abstraction. ICCV 2013: 1529-1536 - [c8]Vibhav Vineet, Carsten Rother, Philip H. S. Torr:
Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes Estimation. NIPS 2013: 557-565 - [i1]Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin, Jonathan Warrell, Vibhav Vineet, Paul Sturgess, Nigel T. Crook, Niloy J. Mitra, Philip H. S. Torr:
ImageSpirit: Verbal Guided Image Parsing. CoRR abs/1310.4389 (2013) - 2012
- [c7]Vibhav Vineet, Jonathan Warrell, Paul Sturgess, Philip H. S. Torr:
Improved Initialization and Gaussian Mixture Pairwise Terms for Dense Random Fields with Mean-field Inference. BMVC 2012: 1-11 - [c6]Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr:
A tiered move-making algorithm for general pairwise MRFs. CVPR 2012: 1632-1639 - [c5]Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr:
Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces. ECCV (5) 2012: 31-44 - 2011
- [c4]Vibhav Vineet, Jonathan Warrell, Lubor Ladicky, Philip H. S. Torr:
Human Instance Segmentation from Video using Detector-based Conditional Random Fields. BMVC 2011: 1-11
2000 – 2009
- 2009
- [c3]Vibhav Vineet, P. J. Narayanan:
Solving Multilabel MRFs Using Incremental alpha-Expansion on the GPUs. ACCV (3) 2009: 633-643 - [c2]Vibhav Vineet, Pawan Harish, Suryakant Patidar, P. J. Narayanan:
Fast minimum spanning tree for large graphs on the GPU. High Performance Graphics 2009: 167-171 - 2008
- [c1]Vibhav Vineet, P. J. Narayanan:
CUDA cuts: Fast graph cuts on the GPU. CVPR Workshops 2008: 1-8
Coauthor Index
Harkirat S. Behl
aka: Harkirat Singh Behl
aka: Harkirat Singh Behl
Yogesh S. Rawat
aka: Yogesh Singh Rawat
aka: Yogesh Singh Rawat
Philip Torr 0001
aka: Philip H. S. Torr
aka: Philip H. S. Torr
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last updated on 2024-10-14 23:32 CEST by the dblp team
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