Okay, here we go.
Neural Volume Rendering for Dynamic Scenes
NeRF has shown incredible view synthesis results, but it requires multi-view captures for STATIC scenes.
How can we achieve view synthesis for DYNAMIC scenes from a single video? Here is what I learned from several recent efforts.
![](https://pbs.twimg.com/ext_tw_video_thumb/1349755952753479682/pu/img/90NrDamTBJXOwmnW.jpg)
Okay, here we go.
NeRF represents the scene as a 5D continuous volumetric scene function that maps the spatial position and viewing direction to color and density. It then projects the colors/densities to form an image with volume rendering.
Volumetric + Implicit -> Awesome!
![](https://pbs.twimg.com/media/ErtSuCoXcAMYQlD.jpg)
Building on NeRF, one can extend it for handling dynamic scenes with two types of approaches.
A) 4D (or 6D with views) function.
One direct approach is to include TIME as an additional input to learn a DYNAMIC radiance field.
e.g., Video-NeRF, NSFF, NeRFlow
![](https://pbs.twimg.com/media/ErtgOm8XAAEevcH.jpg)
Inspired by non-rigid reconstruction methods, this type of approach learns a radiance field in a canonical frame (template) and predicts deformation for each frame to account for dynamics over time.
e.g., Nerfie, NR-NeRF, D-NeRF
![](https://pbs.twimg.com/media/Ertwqi9W8AM08Xw.jpg)
All the methods use an MLP to encode the deformation field. But, how do they differ?
A) INPUT: How to encode the additional time dimension as input?
B) OUTPUT: How to parametrize the deformation field?
One can choose to use EXPLICIT conditioning by treating the frame index t as input.
Alternatively, one can use a learnable LATENT vector for each frame.
![](https://pbs.twimg.com/media/Ert19b4WMAMwPxC.png)
We can either use the MLP to predict
- dense 3D translation vectors (aka scene flow) or
- dense rigid motion field
![](https://pbs.twimg.com/media/Ert3Ej2XYAEsWeR.png)
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The entire discussion around Facebook’s disclosures of what happened in 2016 is very frustrating. No exec stopped any investigations, but there were a lot of heated discussions about what to publish and when.
In the spring and summer of 2016, as reported by the Times, activity we traced to GRU was reported to the FBI. This was the standard model of interaction companies used for nation-state attacks against likely US targeted.
In the Spring of 2017, after a deep dive into the Fake News phenomena, the security team wanted to publish an update that covered what we had learned. At this point, we didn’t have any advertising content or the big IRA cluster, but we did know about the GRU model.
This report when through dozens of edits as different equities were represented. I did not have any meetings with Sheryl on the paper, but I can’t speak to whether she was in the loop with my higher-ups.
In the end, the difficult question of attribution was settled by us pointing to the DNI report instead of saying Russia or GRU directly. In my pre-briefs with members of Congress, I made it clear that we believed this action was GRU.
The story doesn\u2019t say you were told not to... it says you did so without approval and they tried to obfuscate what you found. Is that true?
— Sarah Frier (@sarahfrier) November 15, 2018
In the spring and summer of 2016, as reported by the Times, activity we traced to GRU was reported to the FBI. This was the standard model of interaction companies used for nation-state attacks against likely US targeted.
In the Spring of 2017, after a deep dive into the Fake News phenomena, the security team wanted to publish an update that covered what we had learned. At this point, we didn’t have any advertising content or the big IRA cluster, but we did know about the GRU model.
This report when through dozens of edits as different equities were represented. I did not have any meetings with Sheryl on the paper, but I can’t speak to whether she was in the loop with my higher-ups.
In the end, the difficult question of attribution was settled by us pointing to the DNI report instead of saying Russia or GRU directly. In my pre-briefs with members of Congress, I made it clear that we believed this action was GRU.
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BREAKING: @CommonsCMS @DamianCollins just released previously sealed #Six4Three @Facebook documents:
Some random interesting tidbits:
1) Zuck approves shutting down platform API access for Twitter's when Vine is released #competition
2) Facebook engineered ways to access user's call history w/o alerting users:
Team considered access to call history considered 'high PR risk' but 'growth team will charge ahead'. @Facebook created upgrade path to access data w/o subjecting users to Android permissions dialogue.
3) The above also confirms @kashhill and other's suspicion that call history was used to improve PYMK (People You May Know) suggestions and newsfeed rankings.
4) Docs also shed more light into @dseetharaman's story on @Facebook monitoring users' @Onavo VPN activity to determine what competitors to mimic or acquire in 2013.
https://t.co/PwiRIL3v9x
Some random interesting tidbits:
1) Zuck approves shutting down platform API access for Twitter's when Vine is released #competition
![](https://pbs.twimg.com/media/DtqhSTdU4AAJRnB.jpg)
2) Facebook engineered ways to access user's call history w/o alerting users:
Team considered access to call history considered 'high PR risk' but 'growth team will charge ahead'. @Facebook created upgrade path to access data w/o subjecting users to Android permissions dialogue.
![](https://pbs.twimg.com/media/Dtqkp_ZV4AA2o2b.jpg)
3) The above also confirms @kashhill and other's suspicion that call history was used to improve PYMK (People You May Know) suggestions and newsfeed rankings.
4) Docs also shed more light into @dseetharaman's story on @Facebook monitoring users' @Onavo VPN activity to determine what competitors to mimic or acquire in 2013.
https://t.co/PwiRIL3v9x
![](https://pbs.twimg.com/media/Dtqnj5fUUAIyVPc.jpg)
So friends here is the thread on the recommended pathway for new entrants in the stock market.
Here I will share what I believe are essentials for anybody who is interested in stock markets and the resources to learn them, its from my experience and by no means exhaustive..
First the very basic : The Dow theory, Everybody must have basic understanding of it and must learn to observe High Highs, Higher Lows, Lower Highs and Lowers lows on charts and their
Even those who are more inclined towards fundamental side can also benefit from Dow theory, as it can hint start & end of Bull/Bear runs thereby indication entry and exits.
Next basic is Wyckoff's Theory. It tells how accumulation and distribution happens with regularity and how the market actually
Dow theory is old but
Here I will share what I believe are essentials for anybody who is interested in stock markets and the resources to learn them, its from my experience and by no means exhaustive..
First the very basic : The Dow theory, Everybody must have basic understanding of it and must learn to observe High Highs, Higher Lows, Lower Highs and Lowers lows on charts and their
Even those who are more inclined towards fundamental side can also benefit from Dow theory, as it can hint start & end of Bull/Bear runs thereby indication entry and exits.
![](https://pbs.twimg.com/media/FBvF5FpaIAE1BmC.jpg)
Next basic is Wyckoff's Theory. It tells how accumulation and distribution happens with regularity and how the market actually
Dow theory is old but
Old is Gold....
— Professor (@DillikiBiili) January 23, 2020
this Bharti Airtel chart is a true copy of the Wyckoff Pattern propounded in 1931....... pic.twitter.com/tQ1PNebq7d
A brief analysis and comparison of the CSS for Twitter's PWA vs Twitter's legacy desktop website. The difference is dramatic and I'll touch on some reasons why.
Legacy site *downloads* ~630 KB CSS per theme and writing direction.
6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices
https://t.co/qyl4Bt1i5x
PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.
735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices
https://t.co/w7oNG5KUkJ
The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.
The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.
Legacy site *downloads* ~630 KB CSS per theme and writing direction.
6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices
https://t.co/qyl4Bt1i5x
![](https://pbs.twimg.com/media/DrIk2JhU8AAjf_m.jpg)
PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.
735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices
https://t.co/w7oNG5KUkJ
![](https://pbs.twimg.com/media/DrIk3TjU0AAhf3D.jpg)
The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.
The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.