CVF/ICCV More Exploration, Less Exploitation (MELEX) 2021 Workshop
Computer vision methods are constantly being optimised with waves of exploration and exploitation. During exploration, exciting innovative ideas are proposed, but they have a hard time to get noticed because they do not necessarily beat the state-of-the-art (SOTA) results. During exploitation, researchers tend to fine-tune high-performing approaches to beat the SOTA, where large efforts are needed to obtain relatively small gains.
With the first CVF/ICCV More Exploration, Less Exploitation (MELEX) workshop we aim to publish papers in all areas of computer vision that propose explorative papers with innovative models, algorithms, and ideas that show competitive, but not necessarily the SOTA results in benchmarks.
We call for unpublished innovative papers that have a history of being rejected by the main conferences because they did not achieve SOTA results. We are particularly interested in papers that have not been published, but are already receiving citations in arxiv [Call for Papers]
Your submission must contain:
1) manuscript (Paper format is the same as the one used for the main conference),
2) single-page letter explaining the paper history in terms of submissions, scores and how the authors addressed the reviews.
The submission may also contain supplementary material.
The accepted papers will be published in the ICCV proceedings.
Important Dates
Paper submission deadline: 26 July 2021 EXTENDED TO 2 AUGUST 2021
Notification to authors: 10 August 2021
Camera-ready: 14 August 2021
Workshop: 16 October 2021, Morning.
Invited Speakers
Program (16 October -- times in EDT)
9:00 - 9:10 - Opening Remarks
9:10 - 9:22 - Accepted Paper 1: Duhyeon Bang and Hyunjung Shim. MGGAN: Solving Mode Collapse Using Manifold-Guided Training. [Video]
9:23 - 9:35 - Accepted Paper 2: Max Ehrlich, Larry Davis, Ser-Nam Lim, Abhinav Shrivastava. Analyzing and Mitigating JPEG Compression Defects in Deep Learning. [Video]
9:36 - 9:48 - Accepted Paper 3: Saneem A. Chemmengath, Soumava Paul, Samarth Bharadwaj, Suranjana Samanta, Karthik Sankaranarayanan. Addressing Target Shift in Zero-shot Learning using Grouped Adversarial Learning. [Video]
9:50 - 10:00 - Break
10:35 - 11:05 - Invited speaker: Demetri Terzopoulos
11:10 - 11:40 - Invited Speaker: Angjoo Kanazawa
11:45 - 12:15 - Invited Speaker: Alexei Efros
12:45 - 12:50 - Final remarks
Organisers