Achal Dave

According to our database, Achal Dave authored at least 32 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Detecting clinical medication errors with AI enabled wearable cameras.

Justin Chan, Solomon Nsumba, Mitchell Wortsman, Achal Dave, Ludwig Schmidt, Shyamnath Gollakota, Kelly E. Michaelsen

npj Digit. Medicine, 2024

GRIN: Zero-Shot Metric Depth with Pixel-Level Diffusion.

Vitor Guizilini, Pavel Tokmakov, Achal Dave, Rares Ambrus

CoRR, 2024

Dreamitate: Real-World Visuomotor Policy Learning via Video Generation.

Junbang Liang, Ruoshi Liu, Ege Ozguroglu, Sruthi Sudhakar, Achal Dave, Pavel Tokmakov, Shuran Song, Carl Vondrick

CoRR, 2024

DataComp-LM: In search of the next generation of training sets for language models.

Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

CoRR, 2024

Linearizing Large Language Models.

Jean Mercat, Igor Vasiljevic, Sedrick Keh, Kushal Arora, Achal Dave, Adrien Gaidon, Thomas Kollar

CoRR, 2024

Language models scale reliably with over-training and on downstream tasks.

Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt

CoRR, 2024

Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models.

Wen-Hsuan Chu, Adam W. Harley, Pavel Tokmakov, Achal Dave, Leonidas J. Guibas, Katerina Fragkiadaki

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Generative Camera Dolly: Extreme Monocular Dynamic Novel View Synthesis.

Basile Van Hoorick, Rundi Wu, Ege Ozguroglu, Kyle Sargent, Ruoshi Liu, Pavel Tokmakov, Achal Dave, Changxi Zheng, Carl Vondrick

Proceedings of the Computer Vision - ECCV 2024, 2024

pix2gestalt: Amodal Segmentation by Synthesizing Wholes.

Ege Ozguroglu, Ruoshi Liu, Dídac Surís, Dian Chen, Achal Dave, Pavel Tokmakov, Carl Vondrick

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Understanding Video Transformers via Universal Concept Discovery.

Matthew Kowal, Achal Dave, Rares Ambrus, Adrien Gaidon, Konstantinos G. Derpanis, Pavel Tokmakov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Tracking Any Object Amodally.

Cheng-Yen Hsieh, Tarasha Khurana, Achal Dave, Deva Ramanan

CoRR, 2023

Visual Item Selection With Voice Assistants: A systems perspective.

Prashan Wanigasekara, Rafid Al-Humaimidi, Turan Gojayev, Niloofar Gheissari, Achal Dave, Stephen Rawls, Fan Yang, Kechen Qin, Nalin Gupta, Spurthi Sandiri, Chevanthie Dissanayake, Zeynab Raeesy, Emre Barut, Chengwei Su

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video.

Ali Athar, Jonathon Luiten, Paul Voigtlaender, Tarasha Khurana, Achal Dave, Bastian Leibe, Deva Ramanan

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

HandsOff: Labeled Dataset Generation With No Additional Human Annotations.

Austin Xu, Mariya I. Vasileva, Achal Dave, Arjun Seshadri

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Shape of You: Precise 3D shape estimations for diverse body types.

Rohan Sarkar, Achal Dave, Gerard Medioni, Benjamin Biggs

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP).

Alex Fang, Gabriel Ilharco, Mitchell Wortsman, Yuhao Wan, Vaishaal Shankar, Achal Dave, Ludwig Schmidt

Proceedings of the International Conference on Machine Learning, 2022

Differentiable Raycasting for Self-Supervised Occupancy Forecasting.

Tarasha Khurana, Peiyun Hu, Achal Dave, Jason Ziglar, David Held, Deva Ramanan

Proceedings of the Computer Vision - ECCV 2022, 2022

Opening up Open World Tracking.

Yang Liu, Idil Esen Zulfikar, Jonathon Luiten, Achal Dave, Deva Ramanan, Bastian Leibe, Aljosa Osep, Laura Leal-Taixé

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Towards Long-Tailed 3D Detection.

Neehar Peri, Achal Dave, Deva Ramanan, Shu Kong

Proceedings of the Conference on Robot Learning, 2022

2021

Open-world Object Detection and Tracking.

Achal Dave

PhD thesis, 2021

Deep Learning Based Semi-Blind Tracking for Aging Wireless Communication Channels.

Achal Dave, Sachit Kuhar, Ribhu Chopra

Wirel. Pers. Commun., 2021

Evaluating Large-Vocabulary Object Detectors: The Devil is in the Details.

Achal Dave, Piotr Dollár, Deva Ramanan, Alexander Kirillov, Ross B. Girshick

CoRR, 2021

Do Image Classifiers Generalize Across Time?

Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Detecting Invisible People.

Tarasha Khurana, Achal Dave, Deva Ramanan

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Measuring Robustness to Natural Distribution Shifts in Image Classification.

Rohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

TAO: A Large-Scale Benchmark for Tracking Any Object.

Achal Dave, Tarasha Khurana, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Learning to Track Any Object.

Achal Dave, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan

CoRR, 2019

A systematic framework for natural perturbations from videos.

Vaishaal Shankar, Achal Dave, Rebecca Roelofs, Deva Ramanan, Benjamin Recht, Ludwig Schmidt

CoRR, 2019

Towards Segmenting Everything That Moves.

Achal Dave, Pavel Tokmakov, Deva Ramanan

CoRR, 2019

Towards Segmenting Anything That Moves.

Achal Dave, Pavel Tokmakov, Deva Ramanan

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2017

Predictive-Corrective Networks for Action Detection.

Achal Dave, Olga Russakovsky, Deva Ramanan

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2014

HOBS: head orientation-based selection in physical spaces.

Ben Zhang, Yu-Hsiang Chen, Claire Tuna, Achal Dave, Yang Li, Edward A. Lee, Björn Hartmann

Proceedings of the 2nd ACM Symposium on Spatial User Interaction, 2014